Essay On Diversity And Discrimination In India

Gender inequality in India refers to health, education, economic and political inequalities between men and women in India.[1] Various international gender inequality indices rank India differently on each of these factors, as well as on a composite basis, and these indices are controversial.[2][3]

Gender inequalities, and its social causes, impact India's sex ratio, women's health over their lifetimes, their educational attainment, and economic conditions. Gender inequality in India is a multifaceted issue that concerns men and women alike. Some argue that some gender equality measures, place men at a disadvantage. However, when India's population is examined as a whole, women are at a disadvantage in several important ways. In India, discriminatory attitudes towards either sex have existed for generations and affect the lives of both sexes. Although the constitution of India has granted men and women equal rights, gender disparity still remains.

There is specific research on gender discrimination mostly in favour of men over women in many realms including the workplace.[4][5] While Indian laws on rape, dowry and adultery have women's safety at heart, these highly discriminatory practices are still taking place at an alarming rate, affecting the lives of many today.

Gender statistics[edit]

The following table compares the population wide data for the two genders on various inequality statistical measures, according to The World Bank's Gender Statistics database for 2012.[6]

Gender Statistic Measure[6]Females
Infant mortality rate, (per 1,000 live births)44.343.532.637
Life expectancy at birth, (years)6864.572.968.7
Expected years of schooling11.311.811.712.0
Primary school completion rate, (%)96.696.3[7]
Lower secondary school completion rate, (%)76.077.970.270.5
Secondary school education, pupils (%)465447.652.4
Ratio to males in primary and secondary education (%)0.981.00.971.0
Secondary school education, gender of teachers (% )41.158.951.948.1
Account at a formal financial institution, (% of each gender, age 15+)26.543.746.654.5
Deposits in a typical month, (% with an account, age 15+)11.213.413.012.8
Withdrawals in a typical month, (% with an account, age 15+)18.612.715.512.8
Loan from a financial institution in the past year, (% age 15+)
Outstanding loan from banks for health or emergencies, (% age 15+)12.615.710.311.6
Outstanding loan from banks to purchase a home, (% age 15+)2.262.356.67.4
Unemployment, (% of labour force, ILO method)43.1[7]
Unemployment, youth (% of labour force ages 15–24, ILO method)10.69.415.113.0
Ratio to male youth unemployment rate (% ages 15–24, ILO method)
Employees in agriculture, (% of total labour)59.843[7]
Employees in industry, (% of total labour)20.726[7]
Self-employed, (% employed)85.580.6[7]
Cause of death, by non-communicable diseases, ages 15–34, (%)32.333.029.527.5
Life expectancy at age 60, (years)18.015.9[7]

Global rankings of India[edit]

Various groups have ranked gender inequalities around the world. For example, the World Economic Forum publishes a Global Gender Gap Index score for each nation every year. The index focuses not on empowerment of women, but on the relative gap between men and women in four fundamental categories – economic participation, educational attainment, health and survival, and political empowerment.[8] It includes measures such as estimated sex selective abortion, number of years the nation had a female head of state, female to male literacy rate, estimated income ratio of female to male in the nation, and several other relative gender statistic measures. It does not include factors such as crime rates against women versus men, domestic violence, honor killings or such factors. Where data is unavailable or difficult to collect, World Economic Forum uses old data or makes a best estimate to calculate the nation's Global Gap Index (GGI).[8]

According to the Global Gender Gap Report released by the World Economic Forum (WEF) in 2011, India was ranked 113 on the Gender Gap Index (GGI) among 135 countries polled.[9] Since then, India has improved its rankings on the World Economic Forum's Gender Gap Index (GGI) to 105/136 in 2013.[8] When broken down into components of the GGI, India performs well on political empowerment, but is scored to be as bad as China on sex selective abortion. India also scores poorly on overall female to male literacy and health rankings. India with a 2013 ranking of 101 had an overall score of 0.6551, while Iceland, the nation that topped the list, had an overall score of 0.8731 (no gender gap would yield a score of 1.0).[8]

Alternate measures include OECD's Social Institutions Gender Index (SIGI), which ranked India at 56th out of 86 in 2012, which was an improvement from its 2009 rank of 96th out of 102. The SIGI is a measure of discriminatory social institutions that are drivers of inequalities, rather than the unequal outcomes themselves.[10] Similarly, UNDP has published Gender Inequality Index and ranked India at 132 out of 148 countries.

Problems with indices

Scholars[3][11] have questioned the accuracy, relevance and validity of these indices and global rankings. For example, Dijkstra and Hanmer[2] acknowledge that global index rankings on gender inequality have brought media attention, but suffer from major limitations. The underlying data used to calculate the index are dated, unreliable and questionable. Further, a nation can be and are being ranked high when both men and women suffer from equal deprivation and lack of empowerment.[2] In other words, nations in Africa and the Middle East where women have lower economic participation, lower educational attainment, and poorer health and high infant mortalities, rank high if both men and women suffer from these issues equally. If one's goal is to measure progress, prosperity and empowerment of women with equal gender rights, then these indices are not appropriate for ranking or comparing nations. They have limited validity.[2] Instead of rankings, the focus should be on measuring women's development, empowerment and gender parity, particularly by relevant age groups such as children and youth.[12][13] Nevertheless, it is widely accepted that India along with other developing countries have high gender inequality and low women's empowerment than developed nations.[14][15]


The cultural construct of Indian society which reinforces gender bias against men and women, with varying degrees and variable contexts against the opposite sex,[16] has led to the continuation of India's strong preference for male children. Female infanticide and sex-selective abortion is adopted and strongly reflects the societally low status of Indian women. Census 2011 shows decline of girl population (as a percentage to total population) under the age of seven, with activists estimating that eight million female fetuses may have been aborted in the past decade.[17] The 2005 census shows infant mortality figures for females and males are 61 and 56, respectively, out of 1000 live births,[18] with females more likely to be aborted than males due to biased attitudes, cultural stereotypes, insecurity, etc.

A decline in the child sex ratio (0–6 years) was observed with India's 2011 census reporting that it stands at 914 females against 1,000 males, dropping from 927 in 2001 – the lowest since India's independence.[19]

The demand for sons among wealthy parents is being satisfied by the medical community through the provision of illegal service of fetal sex-determination and sex-selective abortion. The financial incentive for physicians to undertake this illegal activity seems to be far greater than the penalties associated with breaking the law.[20]

Childhood to adulthood and its education[edit]

Education is not wise attained by Indian women. Although literacy rates are increasing, female literacy rate lags behind the male literacy rate.

Literacy for females stands at 65.46%, compared to 82.14% for males.[21] An underlying factor for such low literacy rates are parents' perceptions that education for girls are a waste of resources as their daughters would eventually live with their husbands' families. Thus, there is a strong belief that due to their traditional duty and role as housewives, daughters would not benefit directly from the education investment.[22]

Adulthood and onwards[edit]

Discrimination against women has contributed to gender wage differentials, with Indian women on average earning 64% of what their male counterparts earn for the same occupation and level of qualification.[23]

This has led to their lack of autonomy and authority. Although equal rights are given to women, equality may not be well implemented. In practice, land and property rights are weakly enforced, with customary laws widely practised in rural areas. Women do not own property under their own names and usually do not have any inheritance rights to obtain a share of parental property.[24]

Economic inequalities[edit]

Labour participation and wages[edit]

The labour force participation rate of women was 80.7 in 2013.[25] Nancy Lockwood of Society for Human Resource Management, the world's largest human resources association with members in 140 countries, in a 2009 report wrote that female labour participation is lower than men, but has been rapidly increasing since the 1990s. Out of India's 397 million workers in 2001, 124 million were women, states Lockwood.[26]

Over 50% of Indian labour is employed in agriculture. A majority of rural men work as cultivators, while a majority of women work in livestock maintenance, egg and milk production. Rao[27] states that about 78 percent of rural women are engaged in agriculture, compared to 63 percent of men. About 37% of women are cultivators, but they are more active in the irrigation, weeding, winnowing, transplanting, and harvesting stages of agriculture. About 70 percent of farm work was performed by women in India in 2004.[27] Women's labour participation rate is about 47% in India's tea plantations, 46% in cotton cultivation, 45% growing oil seeds and 39% in horticulture.[28]

There is wage inequality between men and women in India. The largest wage gap was in manual ploughing operations in 2009, where men were paid ₹ 103 per day, while women were paid ₹ 55, a wage gap ratio of 1.87. For sowing the wage gap ratio reduced to 1.38 and for weeding 1.18.[29] For other agriculture operations such as winnowing, threshing and transplanting, the men to female wage ratio varied from 1.16 to 1.28. For sweeping, the 2009 wages were statistically same for men and women in all states of India.[29]

Access to credit[edit]

Although laws are supportive of lending to women and microcredit programs targeted to women are prolific, women often lack collateral for bank loans due to low levels of property ownership and microcredit schemes have come under scrutiny for coercive lending practices. Although many microcredit programs have been successful and prompted community-based women's self-help groups, a 2012 review of microcredit practices found that women are contacted by multiple lenders and as a result, take on too many loans and overextend their credit. The report found that financial incentives for the recruiters of these programs were not in the best interest of the women they purported to serve.[30] The result was a spate of suicides by women who were unable to pay their debts.[31]

Property Rights[edit]

Women have equal rights under the law to own property and receive equal inheritance rights, but in practice, women are at a disadvantage. This is evidenced in the fact that 70% of rural land is owned by men.[citation needed] Laws, such as the Married Women Property Rights Act of 1974 protect women, but few seek legal redress.[32] Although the Hindu Succession Act of 2005 provides equal inheritance rights to ancestral and jointly owned property, the law is weakly enforced, especially in Northern India.

Occupational inequalities[edit]


Different studies have examined the women in entrepreneurship roles and the attitudes and outcomes surrounding their participation in this informal economic sector.[33][34] A 2011 study published by Tarakeswara Rao et al. in the Journal of Commerce indicated that almost 50% of the Indian population consists of women, yet fewer than 5% of businesses are owned by women.[33] In fact, in terms of entrepreneurship as an occupation, 7% of total entrepreneurs in India are women, while the remaining 93% are men.[33] Another 2011 study conducted by Colin Williams and Anjula Gurtoo, published in the International Journal of Gender and Entrepreneurship describes how previous studies have concluded that women entrepreneurs face several barriers in the development of their work.[34] Some of these barriers include lacking access to institutional credit which presents negative consequences in terms of expanding businesses.[34] In addition, women in this realm may lack a formal designated space for their occupational work and can face gendered violence due to their more open presence in society.[34] The other major challenge for women entrepreneurs is the type of activities performed in their occupational role.[34] Often times, these activities may be quite limited, corresponding to traditional gendered roles, performing business ventures such as selling fruit or flowers at temples in India, which hinders the further development of women entrepreneurs beyond a certain point.[34]

This study by Colin Williams and Anjula Gurtoo also gathered data in the form of personal interviews with various women working in a entrepreneurship realm.[34] In the study, the categories of occupation among women entrepreneurs were defined as the following: home helpers, venders, office assistants, and shop assistants.[34] The findings from the study indicated that these entrepreneurial women did not consider job security to be an area of concern like some of their counterparts working in other industries.[34] However, a primary concern for these women was the lack of alternate employment which initially prompted them to pursue entrepreneurial work, though economic benefits were slowly acquired after gaining a foothold in the industry.[34]


Teaching is another area of occupation that has many differences based on male versus female teachers in terms of their overall statistical composition and their impact on education.[35] In one particular 2008 study conducted by Amita Chudgar and Vyjayanthi Sankar, published in Compare described the growth of female teachers over recent years, as teaching had previously been considered to be a dominated field in India in earlier times.[35] In the mid-1970s, female teachers accounted for approximately 25% of the teaching force, and this proportion grew to 43% by 2008.[35] This article also outlined that compared to male teachers, female teachers had lower educational qualifications, though a slightly greater proportion of female teachers received specific teacher training.[35] In addition, on average, more female teachers in the study compared to male teachers had a teaching experience that exceeded ten years.[35]

Scientific Professions[edit]

Within the area of various scientific professions, there are several contributing factors to barriers and discrimination that women in these fields face, though the historical trajectory has indicated improvement over the years.[36][37] An underlying contributing cause to gender discrimination in scientific professions includes traditionally constructed gender-stereotypes about the expectations of women as current or prospective homemakers and mothers, with science and technology being a primarily male-dominated sphere.[36][37] Specifically, one area within scientific occupations where clear gender differences manifest is in faculty at science and technology colleges in terms hiring practices and duties assigned.[36] A 2003 study published by Namrata Gupta et al. in Work, Employment, and Society conducted analysis based on four different reputed science and technology higher institutions in India.[36] The results indicated that 40% of female faculty members felt some form of discrimination in their respective institutions, favoring male faculty members.[36] In addition, in terms of hiring practices, the interview committees of these institutions pose questions to female applicants relating to how family would be balanced with work and why the applicant was interviewing for a position rather than serving as a homemaker.[36] Furthermore, discriminatory hiring practices in favor of men are pursued due to certain beliefs about a questionable commitment level in the work environment for women after becoming married and the idea that men need these positions more than women as males are thought to serve as the primary income providers in the traditional familial structure.[36]

Military service[edit]

Women are not allowed to have combat roles in the armed forces. According to a study carried out on this issue, a recommendation was made that female officers be excluded from induction in close combat arms. The study also held that a permanent commission could not be granted to female officers since they have neither been trained for command nor have they been given the responsibility so far. Although changes are appearing and women are playing important roles in army and the defence minister is also female.[38]

Education inequalities[edit]


India is on target to meet its Millennium Development Goal of gender parity in education by 2015.[39] UNICEF's measure of attendance rate and Gender Equality in Education Index (GEEI) capture the quality of education.[40] Despite some gains, India needs to triple its rate of improvement to reach GEEI score of 95% by 2015 under the Millennium Development Goals.

In rural India girls continue to be less educated than boys.[41] Recently, many studies have investigated underlying factors that contribute to greater or less educational attainment by girls in different regions of India.[42] In one 2017 study performed by Adriana D. Kugler and Santosh Kumar, published in Demography, examined the role of familial size and child composition in terms of gender of the first-born child and others on the educational attainment achieved in a particular family.[42] According to this study, as the family size increased by each additional child after the first, on average there was quarter of a year decrease in overall years of schooling, with this statistic disfavoring female children in the family compared to male children.[42] In addition, the educational level of the mother in the family also plays a role in the educational attainment of the children, with the study indicating that in families with mothers that had a lower educational level, the outcomes tended to more disadvantageous for educational attainment of the children.[42]

Secondary Education[edit]

In examining educational disparities between boys and girls, the transition from primary to secondary education displays an increase in the disparity gap, as a greater number of females compared to males drop out from their educational journey after the age of twelve. [43] A particular 2011 study conducted by Gaurav Siddhu, published in the International Journal of Educational Development, investigated the statistics of dropout in the secondary school transition and its contributing factors in Rural India.[44] The study indicated that among the 20% of students who stopped schooling after primary education, near 70% of these students were females.[44] This study also conducted interviews to determine the factors influencing this dropout in Rural India.[44] The results indicated that most common reasons for girls to stop attending school was the distance of travel and social reasons.[44] In terms of distance of travel, families expressed fear for the safety and security of girls, traveling unaccompanied to school every day.[44] Furthermore, in rural areas the social reasons consisted of how families viewed their daughter's role of belonging in her husband's house after marriage, with plans for the daughter's marriage during the secondary school age in some cases.[44]


Though it is gradually rising, the female literacy rate in India is lower than the male literacy rate.[45] According to Census of India 2011, literacy rate of females is 65.46% compared to males which is 82.14%. Compared to boys, far fewer girls are enrolled in the schools, and many of them drop out.[45] According to the National Sample Survey Data of 1997, only the states of Kerala and Mizoram have approached universal female literacy rates. According to majority of the scholars, the major factor behind the improved social and economic status of women in Kerala is literacy.[45] From 2006-2010, the percent of females who completed at least a secondary education was almost half that of men, 26,6% compared to 50.4%.[25] In the current generation of youth, the gap seems to be closing at the primary level and increasing in the secondary level. In rural Punjab, the gap between girls and boys in school enrollment increases dramatically with age as demonstrated in National Family Health Survey-3 where girls age 15-17 in Punjab are 10% more likely than boys to drop out of school.[46] Although this gap has been reduced significantly, problems still remain in the quality of education for girls where boys in the same family will be sent to higher quality private schools and girls sent to the government school in the village.[47]

Reservations for female students[edit]

Under Non-Formal Education programme, about 40% of the centres in states and 10% of the centres in UTs are exclusively reserved for females.[41] As of 2000, about 0.3 million NFE centres were catering to about 7.42 million children, out of which about 0.12 million were exclusively for girls.[41] Certain state level engineering, medical and other colleges like in Orissa have reserved 30% of their seats for females.[48] The Prime Minister of India and the Planning Commission also vetoed a proposal to set up an Indian Institute of Technology exclusively for females.[49] Although India had witnessed substantial improvements in female literacy and enrolment rate since the 1990s, the quality of education for female remains to be heavily compromised.

Health and survival inequalities[edit]

Main article: Women's health in India

On health and survival measures, international standards consider the birth sex ratio implied sex-selective abortion, and gender inequality between women's and men's life expectancy and relative number of years that women live compared to men in good health by taking into account the years lost to violence, disease, malnutrition or other relevant factors.[50]

Sex-selective abortion[edit]

Main article: Sex-selective abortion

In North America and Europe the birth sex ratio of the population ranges between 103 and 107 boys per 100 girls; in India, China and South Korea, the ratio has been far higher. Women have a biological advantage over men for longevity and survival; however, there have been more men than women in India and other Asian countries.[52][53] This higher sex ratio in India and other countries is considered as an indicator of sex-selective abortion.

The 2011 Census birth sex ratio for its States and Union Territories of India, in 0 to 1 age group, indicated Jammu & Kashmir had birth sex ratio of 128 boys to 100 girls, Haryana of 120, Punjab of 117, and the states of Delhi and Uttarakhand to be 114.[51] This has been attributed to increasing misuse and affordability of foetus sex-determining devices, such as ultrasound scan, the rate of female foeticide is rising sharply in India. Female infanticide (killing of girl infants) is still prevalent in some rural areas.[45]

Patnaik estimates from the birth sex ratio that an expected 15 million girls were not born between 2000 and 2010.[54] MacPherson, in contrast, estimates that sex-selective abortions account for about 100,000 missing girls every year in India.[55]

Girl babies are often killed for several reasons, the most prominent one being financial reasons. The economical reasons include, earning of power as men as are the main income-earners, potential pensions, as when the girl is married she would part ways with her family and the most important one, the payment of dowry. Even though, it is illegal by Indian law to ask for dowry, it is still a common practice in certain socio-economic classes which leads to female infanticide, as the baby girls are seen as an economic burden.[56]

Gender selection and selective abortion were banned in India under Pre-conception and Pre-natal Diagnostics Technique Act in 1994.[57] The practice continues illegally. Other institutional efforts, such as advertisements calling female foeticides a sin by the Health Ministry of India and annual Girl Child Day[58] can be observed to raise status of girls and to combat female infanticide.


Immunisation rates for 2 year olds was 41.7% for girls and 45.3% for boys according to the 2005 National Family Health Survey-3, indicating a slight disadvantage for girls.[59] Malnutrition rates in India are nearly equal in boys and girls.

The male to female suicide ratio among adults in India has been about 2:1.[60] This higher male to female ratio is similar to those observed around the world.[61] Between 1987 and 2007, the suicide rate increased from 7.9 to 10.3 per 100,000,[62] with higher suicide rates in southern and eastern states of India.[63] In 2012, Tamil Nadu, Maharashtra and West Bengal had the highest proportion of female suicides.[60] Among large population states, Tamil Nadu and Kerala had the highest female suicide rates per 100,000 people in 2012.

Some studies in south India have found that gender disadvantages, such as negative attitudes towards women's empowerment are risk factors for suicidal behavior and common mental disorders like anxiety and depression.[64]

Gender-based violence[edit]

See also: Violence against women in India, Rape in India, Acid throwing, Dowry death, and Bride burning

Domestic violence,[66][67] rape and dowry-related violence are sources of gender violence.[45][68] According to the National Crime Records Bureau 2013 annual report, 24,923 rape cases were reported across India in 2012.[69] Out of these, 24,470 were committed by relative or neighbor; in other words, the victim knew the alleged rapist in 98 per cent of the cases.[70] Compared to other developed and developing countries, incidence rates of rape per 100,000 people are quite low in India.[71][72] India records a rape rate of 2 per 100,000 people,[69][73] compared to 8.1 rapes per 100,000 people in Western Europe, 14.7 per 100,000 in Latin America, 28.6 in the United States, and 40.2 per 100,000 in Southern African region.[74]

Other sources of gender violence include those that are dowry-related and honor killings. NCRB report states 8,233 dowry deaths in the country in 2012.[75]Honor killings is violence where the woman's behavior is linked to the honour of her whole family; in extreme cases, family member(s) kill her. Honor killings are difficult to verify, and there is dispute whether social activists are inflating numbers. In most cases, honor killings are linked to the woman marrying someone that the family strongly disapproves of.[76] Some honor killings are the result of extrajudicial decisions made by traditional community elders such as "khap panchayats," unelected village assemblies that have no legal authority. Estimates place 900 deaths per year (or about 1 per million people). Honor killings are found the Northern states of Punjab, Haryana, and Uttar Pradesh.[76]

Political inequalities[edit]

This measure of gender inequality considers the gap between men and women in political decision making at the highest levels.[77]

On this measure, India has ranked in top 20 countries worldwide for many years, with 9th best in 2013 – a score reflecting less gender inequality in India's political empowerment than Denmark, Switzerland, Germany, France and United Kingdom.[78][79] From the prime minister to chief ministers of various states, Indian voters have elected women to its state legislative assemblies and national parliament in large numbers for many decades.

Women turnout during India's 2014 parliamentary general elections was 65.63%, compared to 67.09% turnout for men.[80] In 16 states of India, more women voted than men. A total of 260.6 million women exercised their right to vote in April–May 2014 elections for India's parliament.[80]

India passed 73rd and 74th Constitutional Amendments in 1993, which provides for 33 per cent quotas for women's representation in the local self-government institutions. These Amendments were implemented in 1993. This, suggest Ghani et al., has had strong effects for empowering women in India in many spheres.[81]

Reasons for gender inequalities[edit]

Lorber[82] states that gender inequality has been a historic worldwide phenomena, a human invention and based on gender assumptions. It is linked to kinship rules rooted in cultures and gender norms that organises human social life, human relations, as well as promotes subordination of women in a form of social strata.[82]Amartya Sen highlighted the need to consider the socio-cultural influences that promote gender inequalities[83][84] In India, cultural influences favour the preference for sons for reasons related to kinship, lineage, inheritance, identity, status, and economic security. This preference cuts across class and caste lines, and it discriminates against girls.[85] In extreme cases, the discrimination takes the form of honour killings where families kill daughters or daughters-in-law who fail to conform to gender expectations about marriage and sexuality.[86] When a woman does not conform to expected gender norms she is shamed and humiliated because it impacts both her and her family's honor, and perhaps her ability to marry. The causes of gender inequalities are complex, but a number of cultural factors in India can explain how son preference, a key driver of daughter neglect, is so prevalent.[84][87][88]

Patriarchal society[edit]

Patriarchy is a social system of privilege in which men are the primary authority figures, occupying roles of political leadership, moral authority, control of property, and authority over women and children. Most of India, with some exceptions, has strong patriarchal and patrilineal customs, where men hold authority over female family members and inherit family property and title. Examples of patriarchy in India include prevailing customs where inheritance passes from father to son, women move in with the husband and his family upon marriage, and marriages include a bride price or dowry. This 'inter-generational contract' provides strong social and economic incentives for raising sons and disincentives for raising daughters.[89] The parents of the woman essentially lose all they have invested in their daughter to her husband's family, which is a disincentive for investing in their girls during youth. Furthermore, sons are expected to support their parents in old age and women have very limited ability to assist their own parents.[90]

Son preference[edit]

A key factor driving gender inequality is the preference for sons, as they are deemed more useful than girls. Boys are given the exclusive rights to inherit the family name and properties and they are viewed as additional status for their family. In a survey-based study of 1990s data, scholars[91] found that son are believed to have a higher economic utility as they can provide additional labour in agriculture. Another factor is that of religious practices, which can only be performed by males for their parents' afterlife. All these factors make sons more desirable. Moreover, the prospect of parents 'losing' daughters to the husband's family and expensive dowry of daughters further discourages parents from having daughters.[91][92] Additionally, sons are often the only person entitled to performing funeral rights for their parents.[93] Thus, a combination of factors has shaped the imbalanced view of sexes in India. A 2005 study in Madurai, India, found that old age security, economic motivation, and to a lesser extent, religious obligations, continuation of the family name, and help in business or farm, were key reasons for son preference. In turn, emotional support and old age security were main reasons for daughter preference. The study underscored a strong belief that a daughter is a liability.[94]

Discrimination against girls[edit]

Main article: Discrimination against girls in India

While women express a strong preference for having at least one son, the evidence of discrimination against girls after they are born is mixed. A study of 1990s survey data by scholars[91] found less evidence of systematic discrimination in feeding practices between young boys and girls, or gender based nutritional discrimination in India. In impoverished families, these scholars found that daughters face discrimination in the medical treatment of illnesses and in the administration of vaccinations against serious childhood diseases. These practices were a cause of health and survival inequality for girls. While gender discrimination is a universal phonomena in poor nations, a 2005 UN study found that social norms-based gender discrimination leads to gender inequality in India.[95]


Main articles: Dowry, Dowry law in India, and Dowry death

In India, dowry is the payment in cash or some kind of gifts given to bridegroom's family along with the bride. The practice is widespread across geographic region, class and religions.[96] The dowry system in India contributes to gender inequalities by influencing the perception that girls are a burden on families. Such beliefs limit the resources invested by parents in their girls and limits her bargaining power within the family.[citation needed]

The payment of a dowry has been prohibited under The 1961 Dowry Prohibition Act in Indian civil law and subsequently by Sections 304B and 498a of the Indian Penal Code (IPC).[97] Several studies show that while attitudes of people are changing about dowry, the institution has changed very little, and even continues to prevail.[84][98]

Marriage laws[edit]

Main article: Child marriage in India

Men and women have equal rights within marriage under Indian law, with the exception of all men who are allowed to unilaterally divorce their wife.[95] The legal minimum age for marriage is 18 for women and 21 for men, except for those Indians whose religion is Islam for whom child marriage remains legal under India's Mohammedan personal laws. Child marriage is one of the detriments to empowerment of women.[95]

Discrimination against men[edit]

Main article: Men's rights movement in India

Some men's advocacy groups have complained that the government discriminates against men through the use of overly aggressive laws designed to protect women.[99] Although socially women have been at a disadvantage, Indian laws highly favor women.[100] If a husband commits adultery he will be jailed, but a woman cannot be jailed for adultery and neither will she be punished by the courts.[101][102] There is no recognition of sexual molestation of men and rarely the police stations lodge an First Information Report (FIR); men are considered the culprit by default even if it was the woman that committed sexual abuse against men. Women can jail husband's family for dowry related cases by just filing an FIR.[103] The law IPC 498A demands that the husband's family be considered guilty by default, unless proven otherwise, in other words it implements the doctrine of 'guilty unless proven innocent' defying the universally practiced doctrine of 'innocent until proven guilty'. According to one source, this provision is much abused as only four percent of the cases go to the court and the final conviction rate is as low as two percent.[104][105]Supreme Court of India has found that women are filing false cases under the law IPC 498A and it is ruinng the marriages.[106] Some parents state, "discrimination against girls is no longer rampant and education of their child is really important for them be it a girl or a boy."[107] The Men's rights movement in India call for gender neutral laws, especially in regards to child custody, divorce, sexual harassment, and adultery laws. Men's rights activists state that husbands don't report being attacked by their wives with household utensils because of their ego.[108] These activist petition that there is no evidence to prove that the domestic violence faced by men is less than that faced by women.[109]

Political and legal reforms[edit]

Since its independence, India has made significant strides in addressing gender inequalities, especially in the areas of political participation, education, and legal rights.[10][110] Policies and legal reforms to address gender inequalities have been pursued by the government of India. For instance, the Constitution of India contains a clause guaranteeing the right of equality and freedom from sexual discrimination.[111] India is also signatory to the Convention for the Elimination of All Forms of Discrimination Against Women, or CEDAW.[112] However, the government maintains some reservations about interfering in the personal affairs of any community without the community's initiative and consent.[95] A listing of specific reforms is presented below.

State initiatives to reduce gender inequality[edit]

This section needs expansion. You can help by adding to it.(September 2014)

Different states and union territories of India, in cooperation with the central government, have initiated a number of region-specific programs targeted at women to help reduce gender inequality over the 1989-2013 period. Some of these programs include[95] Swarnajayanti Gram Swarozgar Yojana, Sampoorna Gramin Rozgar Yojana, Awareness Generation Projects for Rural and Poor women, Condensed Course of Education for Adult Women, Kishori Shakti Yojana, Swayamsidha Mahila Mandal Programme,[114] Rashtriya Mahila Kosh, Support to Training and Employment Programme for Women, Swawalamban Programme, Swashakti Project, Swayamsidha Scheme, Mahila Samakhya Programme,[115] Integrated Child Development Services, Balika Samriddhi Yojana, National Programme of Nutritional Support to Primary Education (to encourage rural girls to attend primary school daily), National Programme for Education of Girls at Elementary Level, Sarva Shiksha Abyhiyan, Ladli Laxmi Yojana, Delhi Ladli Scheme and others.[95][116]

Bombay High Court, recently in March 2016 has ruled out a judgement that "Married daughters are also obligated to take care of their parents". This is a very bold step towards breaking the traditional norms of the defined roles in the society. Also this shall also motivate women to be more independent not only for themselves but also for their parents.[citation needed]


See also[edit]


  1. ^ abThe Global Gender Gap Report 2013, World Economic Forum, Switzerland
  2. ^ abcdeDijkstra; Hanmer (2000). "Measuring socio-economic gender inequality: Toward an alternative to the UNDP gender-related development index". Feminist Economics. 6 (2): 41–75. doi:10.1080/13545700050076106. 
  3. ^ abcTisdell, Roy; Ghose (2001). "A critical note on UNDP's gender inequality indices". Journal of Contemporary Asia. 31 (3): 385–399. doi:10.1080/00472330180000231. 
  4. ^Subhash C. Kundu, (2003) "Workforce diversity status: a study of employees' reactions", Industrial Management & Data Systems, Vol. 103 Iss: 4, pp.215 - 226
  5. ^Pande, Astone (2007). "Explaining son preference in rural India: The independent role of structural versus individual factors". Population Research and Policy Review. 
  6. ^ abGender Statistics The World Bank (2012)
  7. ^ abcdefGlobal average data not available
  8. ^ abcd"Global Gender Gap Report 2013". World Economic Forum. Archived from the original on 31 March 2014. Retrieved 31 March 2014. 
  9. ^2011 Gender Gap Report World Economic Forum, page 9
  10. ^ ab"Social Institutions and Gender Index: India Profile". OECD. Retrieved 31 March 2014. 
  11. ^Klasen; Schüler (2011). "Reforming the gender-related development index and the gender empowerment measure: Implementing some specific proposals". Feminist Economics. 17 (1): 1–30. doi
The Gender gap index for India compared to other countries. Gender gap index is one of many multi-dimensional measures of gender inequality. India was scored at 0.66 by World Economic Forum, and ranked 101 out of 136 countries in 2013.[1]
India's Global Rank on various Gender Inequality Indices. These indices are controversial.[2][3]
Literacy rate census of India 2001 and 2011 comparison
Birth sex ratio map for India, boys per 100 girls in 0 to 1 age group according to 2011 census.[51]
Average annual crime rates per 100,000 women in India by its States and Union Territories. Crime rate in this map includes all Indian Penal Code crimes such as rape, sexual assault, insult to modesty, kidnapping, abduction, cruelty by intimate partner or relatives, importation or trafficking of girls, persecution for dowry, dowry deaths, indecency, and all other crimes identified by Indian law.[65]
Dowry death rates per 100,000 people map for Indian States and Union Territories in 2012.


Persistent racial inequality in employment, housing, and a wide range of other social domains has renewed interest in the possible role of discrimination. And yet, unlike in the pre–civil rights era, when racial prejudice and discrimination were overt and widespread, today discrimination is less readily identifiable, posing problems for social scientific conceptualization and measurement. This article reviews the relevant literature on discrimination, with an emphasis on racial discrimination in employment, housing, credit markets, and consumer interactions. We begin by defining discrimination and discussing relevant methods of measurement. We then provide an overview of major findings from studies of discrimination in each of the four domains; and, finally, we turn to a discussion of the individual, organizational, and structural mechanisms that may underlie contemporary forms of discrimination. This discussion seeks to orient readers to some of the key debates in the study of discrimination and to provide a roadmap for those interested in building upon this long and important line of research.

Keywords: race, inequality, measurement, mechanisms, African Americans, racial minorities


According to its most simple definition, racial discrimination refers to unequal treatment of persons or groups on the basis of their race or ethnicity. In defining racial discrimination, many scholars and legal advocates distinguish between differential treatment and disparate impact, creating a two-part definition: Differential treatment occurs when individuals are treated unequally because of their race. Disparate impact occurs when individuals are treated equally according to a given set of rules and procedures but when the latter are constructed in ways that favor members of one group over another (Reskin 1998, p. 32; National Research Council 2004, pp. 39–40). The second component of this definition broadens its scope to include decisions and processes that may not themselves have any explicit racial content but that have the consequence of producing or reinforcing racial disadvantage. Beyond more conventional forms of individual discrimination, institutional processes such as these are important to consider in assessing how valued opportunities are structured by race.

A key feature of any definition of discrimination is its focus on behavior. Discrimination is distinct from racial prejudice (attitudes), racial stereotypes (beliefs), and racism (ideologies) that may also be associated with racial disadvantage (see Quillian 2006). Discrimination may be motivated by prejudice, stereotypes, or racism, but the definition of discrimination does not presume any unique underlying cause.


More than a century of social science interest in the question of discrimination has resulted in numerous techniques to isolate and identify its presence and to document its effects (National Research Council 2004). Although no method is without its limitations, together these techniques provide a range of perspectives that can help to inform our understanding of whether, how, and to what degree discrimination matters in the lives of contemporary American racial minorities.

Perceptions of Discrimination

Numerous surveys have asked African Americans and other racial minorities about their experiences with discrimination in the workplace, in their search for housing, and in other everyday social settings (Schuman et al. 2001). One startling conclusion from this line of research is the frequency with which discrimination is reported. A 2001 survey, for example, found that more than one-third of blacks and nearly 20% of Hispanics and Asians reported that they had personally been passed over for a job or promotion because of their race or ethnicity (Schiller 2004). A 1997 Gallup poll found that nearly half of all black respondents reported having experienced discrimination at least once in one of five common situations in the past month (Gallup Organ. 1997). Further, the frequency with which discrimination is reported does not decline among those higher in the social hierarchy; in fact, middle-class blacks are as likely to perceive discrimination as are working-class blacks, if not more (Feagin & Sikes 1994, Kessler et al. 1990). Patterns of perceived discrimination are important findings in their own right, as research shows that those who perceive high levels of discrimination are more likely to experience depression, anxiety, and other negative health outcomes (Kessler et al. 1990). Furthermore, perceived discrimination may lead to diminished effort or performance in education or the labor market, which itself gives rise to negative outcomes (Ogbu 1991; Steele 1997; Loury 2002, pp. 26–33). What remains unclear from this line of research, however, is to what extent perceptions of discrimination correspond to some reliable depiction of reality. Because events may be misperceived or overlooked, perceptions of discrimination may over- or underestimate the actual incidence of discrimination.

Reports by Potential Discriminators

Another line of social science research focuses on the attitudes and actions of dominant groups for insights into when and how racial considerations come into play. In addition to the long tradition of survey research on racial attitudes and stereotypes among the general population (cf. Schuman et al. 2001, Farley et al. 1994), a number of researchers have developed interview techniques aimed at gauging propensities toward discrimination among employers and other gatekeepers. Harry Holzer has conducted a number of employer surveys in which employers are asked a series of questions about “the last worker hired for a noncollege job,” thereby grounding employers’ responses in a concrete recent experience (e.g., Holzer 1996). In this format, race is asked about as only one incidental characteristic in a larger series of questions concerning this recent employee, thereby reducing the social desirability bias often triggered when the subject of race is highlighted. Likewise, by focusing on a completed action, the researcher is able to document revealed preferences rather than expressed ones and to examine the range of employer, job, and labor market characteristics that may be associated with hiring decisions.

A second prominent approach to investigating racial discrimination in employment has relied on in-depth, in-person interviews, which can be effective in eliciting candid discussions about sensitive hiring issues. Kirschenman & Neckerman (1991), for example, describe employers’ blatant admission of their avoidance of young, inner-city black men in their search for workers. Attributing characteristics such as “lazy” and “unreliable” to this group, the employers included in their study were candid in their expressions of strong racial preferences in considering low wage workers (p. 213; see also Wilson 1996, Moss & Tilly 2001). These in-depth studies have been invaluable in providing detailed accounts of what goes through the minds of employers—at least consciously— as they evaluate members of different groups. However, we must keep in mind that racial attitudes are not always predictive of corresponding behavior (LaPiere 1934, Allport 1954, Pager & Quillian 2005). Indeed, Moss & Tilly (2001) report the puzzling finding that “businesses where a plurality of managers complained about black motivation are more likely to hire black men” (p. 151). Hiring decisions (as with decisions to rent a home or approve a mortgage) are influenced by a complex range of factors, racial attitudes being only one. Where understanding persistent racial prejudice and stereotypes is surely an important goal in and of itself, this approach will not necessarily reveal the extent of discrimination in action.

Statistical Analyses

Perhaps the most common approach to studying discrimination is by investigating inequality in outcomes between groups. Rather than focusing on the attitudes or perceptions of actors that may be correlated with acts of discrimination, this approach looks to the possible consequences of discrimination in the unequal distribution of employment, housing, or other social and economic resources. Using large-scale datasets, researchers can identify systematic disparities between groups and chart their direction over time. Important patterns can also be detected through detailed and systematic case studies of individual firms, which often provide a richer array of indicators with which to assess patterns of discrimination (e.g., Castilla 2008, Petersen & Saporta 2004, Fernandez & Friedrich 2007).

Discrimination in statistical models is often measured as the residual race gap in any outcome that remains after controlling for all other race-related influences. Differences may be identified through the main effect of race, suggesting a direct effect of race on an outcome of interest, or through an interaction between race and one or more human capital characteristics, suggesting differential returns to human capital investments on the basis of race (Oaxaca 1973; National Research Council 2004, chapter 7). The main liability of this approach is that it is difficult to effectively account for the multitude of factors relevant to unequal outcomes, leaving open the possibility that the disparities we attribute to discrimination may in fact be explained by some other unmeasured cause(s). In statistical analyses of labor market outcomes, for example, even after controlling for standard human capital variables (e.g., education, work experience), a whole host of employment-related characteristics typically remain unaccounted for. Characteristics such as reliability, motivation, interpersonal skills, and punctuality, for example, are each important to finding and keeping a job, but these are characteristics that are often difficult to capture with survey data (see, for example, Farkas & Vicknair 1996, Farkas 2003). Complicating matters further, some potential control variables may themselves be endogenous to the process under investigation. Models estimating credit discrimination, for example, typically include controls for asset accumulation and credit history, which may themselves be in part the byproduct of discrimination (Yinger 1998, pp. 26–27). Likewise, controls for work experience or firm tenure may be endogenous to the process of employment discrimination if minorities are excluded from those opportunities necessary to building stable work histories (see Tomaskovic-Devey et al. 2005). While statistical models represent an extremely important approach to the study of race differentials, researchers should use caution in making causal interpretations of the indirect measures of discrimination derived from residual estimates. For a more detailed discussion of the challenges and possibilities of statistical approaches to measuring discrimination, see the National Research Council (2004, chapter 7).

Experimental Approaches to Measuring Discrimination

Experimental approaches to measuring discrimination excel in exactly those areas in which statistical analyses flounder. Experiments allow researchers to measure causal effects more directly by presenting carefully constructed and controlled comparisons. In a laboratory experiment by Dovidio & Gaertner (2000), for example, subjects (undergraduate psychology students) took part in a simulated hiring experiment in which they were asked to evaluate the application materials for black and white job applicants of varying qualification levels. When applicants were either highly qualified or poorly qualified for the position, there was no evidence of discrimination. When applicants had acceptable but ambiguous qualifications, however, participants were nearly 70% more likely to recommend the white applicant than the black applicant (see also Biernat & Kobrynowicz’s 1997 discussion of shifting standards).1

Although laboratory experiments offer some of the strongest evidence of causal relationships, we do not know the extent to which their findings relate to the kinds of decisions made in their social contexts—to hire, to rent, to move, for example—that are most relevant to understanding the forms of discrimination that produce meaningful social disparities. Seeking to bring more realism to the investigation, some researchers have moved experiments out of the laboratory and into the field. Field experiments offer a direct measure of discrimination in real-world contexts. In these experiments, typically referred to as audit studies, researchers carefully select, match, and train individuals (called testers) to play the part of a job/apartment-seeker or consumer. By presenting equally qualified individuals who differ only by race or ethnicity, researchers can assess the degree to which racial considerations affect access to opportunities. Audit studies have documented strong evidence of discrimination in the context of employment (for a review, see Pager 2007a), housing searches (Yinger 1995), car sales (Ayres & Siegelman 1995), applications for insurance (Wissoker et al. 1998), home mortgages (Turner & Skidmore 1999), the provision of medical care (Schulman et al. 1999), and even in hailing taxis (Ridley et al. 1989).

Although experimental methods are appealing in their ability to isolate causal effects, they nevertheless suffer from some important limitations. Critiques of the audit methodology have focused on questions of internal validity (e.g., experimenter effects, the problems of effective tester matching), generalizability (e.g., the use of overqualified testers, the limited sampling frame for the selection of firms to be audited), and the ethics of audit research (see Heckman 1998, Pager 2007a for a more extensive discussion of these issues). In addition, audit studies are often costly and difficult to implement and can only be used for selective decision points (e.g., hiring decisions but not training, promotion, termination, etc.).

Studies of Law and Legal Records

Since the civil rights era, legal definitions and accounts of discrimination have been central to both popular and scholarly understandings of discrimination. Accordingly, an additional window into the dynamics of discrimination involves the use of legal records from formal discrimination claims. Whether derived from claims to the Equal Employment Opportunity Commission (EEOC), the courts, or state-level Fair Employment/Fair Housing Bureaus, official records documenting claims of discrimination can provide unique insight into the patterns of discrimination and antidiscrimination enforcement in particular contexts and over time.

Roscigno (2007), for example, analyzed thousands of “serious claims” filed with the Civil Rights Commission of Ohio related to both employment and housing discrimination. These claims document a range of discriminatory behaviors, from harassment, to exclusion, to more subtle forms of racial bias. [See also Harris et al. (2005) for a similar research design focusing on federal court claims of consumer discrimination.] Although studies relying on formal discrimination claims necessarily overlook those incidents that go unnoticed or unreported, these records provide a rare opportunity to witness detailed descriptions of discrimination events across a wide range of social domains not typically observed in conventional research designs.

Other studies use discrimination claims, not to assess patterns of discrimination, but to investigate trends in the application of antidiscrimination law. Nielsen & Nelson (2005) provide an overview of research in this area, examining the pathways by which potential claims (or perceived discrimination) develop into formal legal action, or conversely the many points at which potential claims are deflected from legal action. Hirsh & Kornrich (2008) examine how characteristics of the workplace and institutional environment affect variation in the incidence of discrimination claims and their verification by EEOC investigators. Donohue & Siegelman (1991, 2005) analyze discrimination claims from 1970 through 1997 to chart changes in the nature of antidiscrimination enforcement over time. The overall volume of discrimination claims increased substantially over this period, though the composition of claims shifted away from an emphasis on racial discrimination toward a greater emphasis on gender and disability discrimination. Likewise, the types of employment discrimination claims have shifted from an emphasis on hiring discrimination to an overwhelming emphasis on wrongful termination, and class action suits have become increasingly rare. The authors interpret these trends not as indicators of changes in the actual distribution of discrimination events, but rather as reflections of the changing legal environment in which discrimination cases are pursued (including, for example, changes to civil rights law and changes in the receptivity of the courts to various types of discrimination claims), which themselves may have implications for the expression of discrimination (Donohue & Siegelman 1991, 2005).

Finally, a number of researchers have exploited changes in civil rights and antidiscrimination laws as a source of exogenous variation through which to measure changes in discrimination (see Holzer & Ludwig 2003). Freeman (1973, see table 6 therein), for example, investigates the effectiveness of federal EEO laws by comparing the black-white income gap before and after passage of the Civil Rights Act of 1964. Heckman & Payner (1989) use microdata from textile plants in South Carolina to study the effects of race on employment between 1940 and 1980, concluding that federal antidiscrimination policy resulted in a significant improvement in black economic status between 1965 and 1975. More recent studies exploiting changes in the legal context include Kelly & Dobbin (1998), who examine the effects of changing enforcement regimes on employers’ implementation of diversity initiatives; Kalev & Dobbin (2006), who examine the relative impact of compliance reviews and lawsuits on the representation of women and minorities in management positions; and a volume edited by Skrentny (2001), which examines many of the complex and unexpected facets related to the rise, expansion, and impact of affirmative action and diversity policies in the United States and internationally.

Although no research method is without flaws, careful consideration of the range of methods available helps to match one’s research question with the appropriate empirical strategy. Comparisons across studies can help to shed light on the relative strengths and weaknesses of existing methodological approaches (see National Research Council 2004). At the same time, one must keep in mind that the nature of discrimination may itself be a moving target, with the forms and patterns of discrimination shifting over time and across domains (see Massey 2005, p. 148). These complexities challenge our traditional modes of operationalization and encourage us to continue to update and refine our measures to allow for an adequate accounting of contemporary forms of racial discrimination.


Simple as it may be, one basic question that preoccupies the contemporary literature on discrimination centers around its continuing relevance. Whereas 50 years ago acts of discrimination were overt and widespread, today it is harder to assess the degree to which everyday experiences and opportunities may be shaped by ongoing forms of discrimination. Indeed, the majority of white Americans believe that a black person today has the same chance at getting a job as an equally qualified white person, and only a third believe that discrimination is an important explanation for why blacks do worse than whites in income, housing, and jobs (Pager 2007a). Academic literature has likewise questioned the relevance of discrimination for modern-day outcomes, with the rising importance of skill, structural changes in the economy, and other nonracial factors accounting for increasing amounts of variance in individual outcomes (Heckman 1998, Wilson 1978). Indeed, discrimination is not the only nor even the most important factor shaping contemporary opportunities. Nevertheless, it is important to understand when and how discrimination does play a role in the allocation of resources and opportunities. In the following discussion, we examine the evidence of discrimination in four domains: employment, housing, credit markets, and consumer markets. Although not an exhaustive review of the literature, this discussion aims to identify the major findings and debates within each of these areas of research.


Although there have been some remarkable gains in the labor force status of racial minorities, significant disparities remain. African Americans are twice as likely to be unemployed as whites (Hispanics are only marginally so), and the wages of both blacks and Hispanics continue to lag well behind those of whites (author’s analysis of Current Population Survey, 2006). A long line of research has examined the degree to which discrimination plays a role in shaping contemporary labor market disparities.

Experimental audit studies focusing on hiring decisions have consistently found strong evidence of racial discrimination, with estimates of white preference ranging from 50% to 240% (Cross et al. 1989, Turner et al. 1991, Fix & Struyk 1993, Bendick et al. 1994; see Pager 2007a for a review). For example, in a study by Bertrand & Mullainathan (2004), the researchers mailed equivalent resumes to employers in Boston and Chicago using racially identifiable names to signal race (for example, names like Jamal and Lakisha signaled African Americans, while Brad and Emily were associated with whites).2 White names triggered a callback rate that was 50% higher than that of equally qualified black applicants. Further, their study indicated that improving the qualifications of applicants benefited white applicants but not blacks, thus leading to a wider racial gap in response rates for those with higher skill.

Statistical studies of employment outcomes likewise reveal large racial disparities unaccounted for by observed human capital characteristics. Tomaskovic-Devey et al. (2005) present evidence from a fixed-effects model indicating that black men spend significantly more time searching for work, acquire less work experience, and experience less stable employment than do whites with otherwise equivalent characteristics. Wilson et al. (1995) find that, controlling for age, education, urban location, and occupation, black male high school graduates are 70% more likely to experience involuntary unemployment than whites with similar characteristics and that this disparity increases among those with higher levels of education. At more aggregate levels, research points to the persistence of occupational segregation, with racial minorities concentrated in jobs with lower levels of stability and authority and with fewer opportunities for advancement (Parcel & Mueller 1983, Smith 2002). Of course, these residual estimates cannot control for all relevant factors, such as motivation, effort, access to useful social networks, and other factors that may produce disparities in the absence of direct discrimination. Nevertheless, these estimates suggest that blacks and whites with observably similar human capital characteristics experience markedly different employment outcomes.

Unlike the cases of hiring and employment, research on wage disparities comes to more mixed conclusions. An audit study by Bendick et al. (1994) finds that, among those testers who were given job offers, whites were offered wages that were on average 15 cents/hour higher than their equally qualified black test partners; audit studies in general, however, provide limited information on wages, as many testers never make it to the wage setting stage of the employment process. Some statistical evidence comes to similar conclusions. Cancio et al. (1996), for example, find that, controlling for parental background, education, work experience, tenure, and training, white men earn roughly 15% more than comparable blacks (white women earned 6% more than comparable black women). Farkas & Vicknair (1996), however, using a different dataset, find that the addition of controls for cognitive ability eliminates the racial wage gap for young black and white full-time workers. According to the authors, these findings suggest that racial differences in labor market outcomes are due more to factors that precede labor market entry (e.g., skill acquisition) rather than discrimination within the labor market (see also Neal & Johnson 1996).

Overall, then, the literature points toward consistent evidence of discrimination in access to employment, but less consistent evidence of discrimination in wages. Differing methodologies and/or model specification may account for some of the divergent results. But there is also reason to believe that the processes affecting access to employment (e.g., the influence of first impressions, the absence of more reliable information on prospective employees, and minimal legal oversight) may be more subject to discriminatory decision making than those affecting wages. Further, the findings regarding employment and wages may be in part causally related, as barriers to labor market entry will lead to a more select sample of black wage earners, reducing measured racial disparities (e.g., Western & Pettit 2005). These findings point to the importance of modeling discrimination as a process rather than a single-point outcome, with disparities in premarket skills acquisition, barriers to labor market entry, and wage differentials each part of a larger employment trajectory and shaped to differing degrees by discrimination.


Residential segregation by race remains a salient feature of contemporary American cities. Indeed, African Americans were as segregated from whites in 1990 as they had been at the start of the twentieth century, and levels of segregation appear unaffected by rising socioeconomic status (Massey & Denton 1993). Although segregation appears to have modestly decreased between 1980 and 2000 (Logan et al. 2004), blacks (and to a lesser extent other minority groups) continue to experience patterns of residential placement markedly different from whites. The degree to which discrimination contributes to racial disparities in housing has been a major preoccupation of social scientists and federal housing agents (Charles 2003).

The vast majority of the work on discrimination in housing utilizes experimental audit data. For example, between 2000 and 2002 the Department of Housing and Urban Development conducted an extensive series of audits measuring housing discrimination against blacks, Latinos, Asians, and Native Americans, including nearly 5500 paired tests in nearly 30 metropolitan areas [see Turner et al. (2002), Turner & Ross (2003a); see also Hakken (1979), Feins & Bratt (1983), Yinger (1986), Roychoudhury & Goodman (1992, 1996) for additional, single-city audits of housing discrimination]. The study results reveal bias across multiple dimensions, with blacks experiencing consistent adverse treatment in roughly one in five housing searches and Hispanics experiencing consistent adverse treatment in roughly one out of four housing searches (both rental and sales).3 Measured discrimination took the form of less information offered about units, fewer opportunities to view units, and, in the case of home buyers, less assistance with financing and steering into less wealthy communities and neighborhoods with a higher proportion of minority residents.

Generally, the results of the 2000 Housing Discrimination Study indicate that aggregate levels of discrimination against blacks declined modestly in both rentals and sales since 1989 (although levels of racial steering increased). Discrimination against Hispanics in housing sales declined, although Hispanics experienced increasing levels of discrimination in rental markets.

Other research using telephone audits further points to a gender and class dimension of racial discrimination in which black women and/or blacks who speak in a manner associated with a lower-class upbringing suffer greater discrimination than black men and/or those signaling a middle-class upbringing (Massey & Lundy 2001, Purnell et al. 1999). Context also matters in the distribution of discrimination events (Fischer & Massey 2004). Turner & Ross (2005) report that segregation and class steering of blacks occurs most often when either the housing or the office of the real estate agent is in a predominantly white neighborhood. Multi-city audits likewise suggest that the incidence of discrimination varies substantially across metropolitan contexts (Turner et al. 2002).

Moving beyond evidence of exclusionary treatment, Roscigno and colleagues (2007) provide evidence of the various forms of housing discrimination that can extend well beyond the point of purchase (or rental agreement). Examples from a sample of discrimination claims filed with the Civil Rights Commission of Ohio point to the failure of landlords to provide adequate maintenance for housing units, to harassment or physical threats by managers or neighbors, and to the unequal enforcement of a residential association’s rules.

Overall, the available evidence suggests that discrimination in rental and housing markets remains pervasive. Although there are some promising signs of change, the frequency with which racial minorities experience differential treatment in housing searches suggests that discrimination remains an important barrier to residential opportunities. The implications of these trends for other forms of inequality (health, employment, wealth, and inheritance) are discussed below.

Credit Markets

Whites possess roughly 12 times the wealth of African Americans; in fact, whites near the bottom of the income distribution possess more wealth than blacks near the top of the income distribution (Oliver & Shapiro 1997, p. 86). Given that home ownership is one of the most significant sources of wealth accumulation, patterns that affect the value and viability of home ownership will have an impact on wealth disparities overall. Accordingly, the majority of work on discrimination in credit markets focuses on the specific case of mortgages.

Available evidence suggests that blacks and Hispanics face higher rejection rates and less favorable terms in securing mortgages than do whites with similar credit characteristics (Ross & Yinger 1999). Oliver & Shapiro (1997, p. 142) report that blacks pay more than 0.5% higher interest rates on home mortgages than do whites and that this difference persists with controls for income level, date of purchase, and age of buyer.

The most prominent study of the effect of race on rejection rates for mortgage loans is by Munnell et al. (1996), which uses 1991 Home Mortgage Disclosure Act data supplemented by data from the Federal Reserve Bank of Boston, including individual applicants’ financial, employment, and property background variables that lenders use to calculate the applicants’ probability of default. Accounting for a range of variables linked to risk of default, cost of default, loan characteristics, and personal and neighborhood characteristics, they find that black and Hispanic applications were 82% more likely to be rejected than were those from similar whites. Critics argued that the study was flawed on the basis of the quality of the data collected (Horne 1994), model specification problems (Glennon & Stengel 1994), omitted variables (Zandi 1993, Liebowitz 1993, Horne 1994, Day & Liebowitz 1996), and endogenous explanatory variables (see Ross & Yinger 1999 for a full explication of the opposition), although rejoinders suggest that the race results are affected little by these modifications (Ross & Yinger 1999; S.L. Ross & G.M.B. Tootell, unpublished manuscript).

Audit research corroborates evidence of mortgage discrimination, finding that black testers are less likely to receive a quote for a loan than are white testers and that they are given less time with the loan officer, are quoted higher interest rates, and are given less coaching and less information than are comparable white applicants (for a review, see Ross & Yinger 2002).

In addition to investigating the race of the applicant, researchers have investigated the extent to which the race of the neighborhood affects lending decisions, otherwise known as redlining. Although redlining is a well-documented factor in the origins of contemporary racial residential segregation (see Massey & Denton 1993), studies after the 1974 Equal Credit Opportunity Act, which outlawed redlining, and since the 1977 Community Reinvestment Act, which made illegal having a smaller pool of mortgage funds available in minority neighborhoods than in similar white neighborhoods, find little evidence of its persistence (Benston & Horsky 1991, Schafer & Ladd 1981, Munnell et al. 1996). This conclusion depends in part, however, on one’s definition of neighborhood-based discrimination. Ross & Yinger (1999) distinguish between process-based and outcome-based redlining, with process-based redlining referring to “whether the probability that a loan application is denied is higher in minority neighborhoods than in white neighborhoods, all else equal” whereas outcome-based redlining refers to smaller amounts of mortgage funding available to minority neighborhoods relative to comparable white neighborhoods. Although evidence on both types of redlining is mixed, several studies indicate that, controlling for demand, poor and/or minority neighborhoods have reduced access to mortgage funding, particularly from mainstream lenders (Phillips-Patrick & Rossi 1996, Siskin & Cupingood 1996; see also Ladd 1998 for methodological issues in measuring redlining).

As a final concern, competition and deregulation of the banking industry have led to greater variability in conditions of loans, prompting the label of the “new inequality” in lending (Williams et al. 2005, Holloway 1998). Rather than focusing on rejection rates, these researchers focus on the terms and conditions of loans, in particular whether a loan is favorable or subprime (Williams et al. 2005, Apgar & Calder 2005, Squires 2003). Immergluck & Wiles (1999) have called this the “dual-mortgage market” in which prime lending is given to higher income and white areas, while subprime and predatory lending is concentrated in lower-income and minority communities (see also Dymski 2006, pp. 232–36). Williams et al. (2005), examining changes between 1993 and 2000, find rapid gains in loans to under-served markets from specialized lenders: 78% of the increase in lending to minority neighborhoods was from subprime lenders, and 72% of the increase in refinance lending to blacks was from subprime lenders. Further, the authors find that “even at the highest income level, blacks are almost three times as likely to get their loans from a subprime lender as are others” (p. 197; see also Calem et al. 2004). Although the disproportionate rise of subprime lending in minority communities is not solely the result of discrimination, some evidence suggests that in certain cases explicit racial targeting may be at work. In two audit studies in which creditworthy testers approached sub-prime lenders, whites were more likely to be referred to the lenders’ prime borrowing division than were similar black applicants (see Williams et al. 2005). Further, subprime lenders quoted the black applicants very high rates, fees, and closing costs that were not correlated with risk (Williams et al. 2005).4

Not all evidence associated with credit market discrimination is bad news. Indeed, between 1989 and 2000 the number of mortgage loans to blacks and Hispanics nationwide increased 60%, compared with 16% for whites, suggesting that some convergence is taking place (Turner et al. 2002). Nevertheless, the evidence indicates that blacks and Hispanics continue to face higher rejection rates and receive less favorable terms than whites of equal credit risk. At the time of this writing, the U.S. housing market is witnessing high rates of loan defaults and foreclosures, resulting in large part from the rise in unregulated subprime lending; the consequences of these trends for deepening racial inequalities have yet to be fully explored.

Consumer Markets

Relative to employment, housing, and credit markets, far less research focuses on discrimination in consumer transactions. Nevertheless, there are some salient disparities. A 2005 report by New Jersey Citizen Action using data from two New Jersey lawsuits found that, between 1993 and 2000, blacks and Hispanics were disproportionately subject to financing markup charges at car dealerships, with minority customers paying an average of $339 more than whites with similar credit histories. Harris et al. (2005) analyze federal court cases of consumer discrimination filed from 1990 to 2002, examining the dimensions of subtle and overt degradation (including extended waiting periods, prepay requirements, and higher prices, as well as increased surveillance and verbal and/or physical attacks) and subtle and overt denial of goods and services. They report cases filed in hotels, restaurants, gas stations, grocery/food stores, clothing stores, department stores, home improvement stores, and office equipment stores filed by members of many racial minority groups. Likewise, Feagin & Sikes (1994) document the myriad circumstances in which their middle-class African American respondents report experiences of discrimination, ranging from poor service in restaurants to heightened surveillance in department stores to outright harassment in public accommodations. Together, these studies suggest that discrimination in consumer markets continues to impose both psychic and financial costs on minority consumers.

Much of the empirical work on discrimination in consumer markets has focused specifically on the case of car purchases, which, aside from housing, represent one of the most significant forms of personal consumption expenditures (Council of Economic Advisers 1997, table B-14).5Ayres & Siegelman (1995) conducted an audit study in Chicago in which testers posed as customers seeking to purchase a new car, approaching dealers with identical rehearsed bargaining strategies. The results show that dealers were less flexible in their negotiations with blacks, resulting in a significant disparity in the ultimate distribution of prices (relative to white men, black men and black women paid on average $1132 and $446 more, respectively) (Ayres 1995). Although analyses using microdata have come to more mixed conclusions about the relevance of race in actual car purchase prices (see Goldberg 1996, Morton et al. 2003), the audit evidence suggests that simply equating information, strategy, and credit background is insufficient to eliminate the effects of race on a customer’s bargaining position.

Although much of the literature on consumer discrimination focuses on the race of the individual customer, a few studies have also investigated the effects of community characteristics on the pricing of goods and services. Graddy (1997), for example, investigated discrimination in pricing among fast food chains on the basis of the race and income characteristics of a local area. Using information about prices from over 400 fast food restaurants, matched with 1990 census data for zip code–level income, race, crime, and population density, and controlling for a host of neighborhood, business, and state-level characteristics, the author finds that a 50% increase in a zip code’s percent black is associated with a 5% increase in the price of a meal, corresponding to roughly 15 cents per meal. The study is a useful example of how discrimination, especially in consumer markets, might be examined as a function of segregated residential patterns, suggesting a more contextualized approach to studying discrimination (see also Moore & Roux 2006).

Evidence of consumer discrimination points to a range of situations in which minority customers receive poorer service or pay more than their white counterparts. Although few individual incidents represent debilitating experiences in and of themselves, the accumulation of such experiences over a lifetime may represent an important source of chronic stress (Kessler et al. 1990) or distrust of mainstream institutions (Feagin & Sikes 1994, Bobo & Thompson 2006). Indeed, the cumulative costs of racial discrimination are likely to be far higher than any single study can document.


Measuring the prevalence of discrimination is difficult; identifying its causes is far more so. Patterns of discrimination can be shaped by influences at many different levels, and the specific mechanisms at work are often difficult to observe. Following Reskin (2003), in this discussion we consider influences that operate at the individual, organizational, and societal level. Each level of analysis contains its own range of dynamics that may instigate or mediate expressions of discrimination. Although by no means an exhaustive catalog, this discussion provides some insight into the range of factors that may underlie various forms of discriminatory behavior.

Intrapsychic Factors

Much of the theoretical work on discrimination aims to understand what motivates actors to discriminate along racial lines. Although internal motivations are difficult to measure empirically (Reskin 2003), their relevance to the understanding and conceptualization of discrimination has been central (Quillian 2006). Classical works in this area emphasized the role of prejudice or racial animus as key underpinnings of discrimination, with feelings and beliefs about the inferiority or undesirability of certain racial groups associated with subsequent disadvantaging behavior (Allport 1954, Pettigrew 1982). Conceptualizations of prejudice range from individual-level factors, such as an authoritarian personality (Adorno et al. 1950) or a “taste for discrimination” (Becker 1957), to more instrumental concerns over group competition and status closure (Blumer 1958, Blalock 1956, Jackman 1994, Tilly 1998).

Scholars have characterized changes in the nature of racial prejudice over the past 50 years—as expressed through racial attitudes— as shifting toward the endorsement of equal treatment by race and a repudiation of overt forms of prejudice and discrimination (Schuman et al. 2001). Some, however, question the degree to which these visible changes reflect the true underlying sentiments of white Americans or rather a more superficial commitment to racial equality. Theories of “symbolic racism” (Kinder & Sears 1981), “modern racism” (McConahay 1986), and “laissez-faire racism” (Bobo et al. 1997), for example, each point to the disconnect between attitudes of principle (e.g., racial equality as an ideal) and policy attitudes (e.g., government action to achieve those ideals) as indicative of limited change in underlying racial attitudes (but see Sniderman et al. 1991 for a countervailing view). These new formulations of prejudice include a blending of negative affect and beliefs about members of certain groups with more abstract political ideologies that reinforce the status quo.

Whereas sociological research on prejudice is based largely on explicit attitudes measured through large-scale surveys, psychologists have increasingly turned to measures of implicit prejudice, or forms of racial bias that operate without conscious awareness yet can influence cognition, affect, and behavior (Greenwald & Banaji 1995, Fazio & Olson 2003). Experiments in which subjects are unconsciously primed with words or images associated with African Americans reveal strong negative racial associations, even among those who consciously repudiate prejudicial beliefs. Whereas the links between explicit and implicit forms of prejudice and between implicit prejudice and behavior remain less well understood, the presence of widespread unconscious racial biases has been firmly established across a multitude of contexts (see Lane et al. 2007).

Parallel to the study of racial prejudice (the more affective component of racial attitudes) is a rich history of research on racial stereotypes (a more cognitive component). Whereas many general racial attitudes have shifted toward more egalitarian beliefs, the content and valence of racial stereotypes appears to have changed little over time (Devine & Elliot 1995, Lane et al. 2007).6 White Americans continue to associate African Americans with characteristics such as lazy, violence-prone, and welfare-dependent and Hispanics with characteristics such as poor, unintelligent, and unpatriotic (Smith 1991, Bobo & Kluegel 1997). Culturally embedded stereotypes about racial differences are reflected in both conscious and unconscious evaluations (Greenwald & Banaji 1995) and may set the stage for various forms of discriminatory treatment (Farley et al. 1994).

Researchers differ in perspectives regarding the cognitive utility and accuracy of stereotypes. Whereas many social psychologists view stereotypes as “faulty or inflexible generalization[s]” (Allport 1954), economic theories of statistical discrimination emphasize the cognitive utility of group estimates as a means of dealing with the problems of uncertainty (Phelps 1972, Arrow 1972). Group-level estimates of difficult-to-observe characteristics (such as average productivity levels or risk of loan default) may provide useful information in the screening of individual applicants. Although some important research questions the accuracy of group-level estimates (e.g., Bielby & Baron 1986), the mechanism proposed in models of statistical discrimination—rational actors operating under conditions of uncertainty—differ substantially from those based on racial prejudice. Indeed, much of the literature across the various domains discussed above attempts to discern whether discrimination stems primarily from racial animus or from these more instrumental adaptations to information shortages (e.g., Ayres & Siegelman 1995).

The various factors discussed here, including prejudice, group competition, modern racism, stereotypes, and statistical discrimination, represent just a few of the varied intrapsychic influences that may affect discrimination. It is important to emphasize, however, that the behavioral manifestation of discrimination does not allow one readily to assume any particular underlying intrapsychic motivation, just as a lack of discrimination does not presume the absence of prejudice (see Merton 1970). Continued efforts to measure the processes by which internal states translate into discriminatory action [or what Reskin (2003) calls a shift from “motives” to “mechanisms”] will help to illuminate the underlying causes of contemporary racial discrimination.

Organizational Factors

Beyond the range of interpersonal and intrapsychic factors that may influence discrimination, a large body of work directs our attention toward the organizational contexts in which individual actors operate. Baron & Bielby’s (1980) classic article established a central role for organizations in stratification research, arguing for a framework that links “the ‘macro’ and ‘micro’ dimensions of work organization and inequality” (p. 738). More recent theoretical and empirical advances in the field of discrimination have maintained a strong interest in the role of organizations as a key structural context shaping inequality.

Tilly’s (1998) analysis of durable inequality emphasizes the importance of organizational dynamics in creating and maintaining group boundaries. “Durable inequality arises because people who control access to value-producing resources solve pressing organizational problems by means of categorical distinctions” (p. 8). Although actors “rarely set out to manufacture inequality as such,” their efforts to secure access to valued resources by distinguishing between insiders and outsiders, ensuring solidarity and loyalty, and monopolizing important knowledge often make use of (and thereby reinforce the salience of) established categories in the service of facilitating organizational goals (p. 11). Tilly’s analysis places organizational structure at the center stage, arguing that “the reduction or intensification of racist, sexist, or xenophobic attitudes will have relatively little impact on durable inequality, whereas the introduction of new organizational forms … will have great impact” (p. 15). In line with these arguments, an important line of sociological research has sought to map the dimensions of organizational structures that may attenuate or exacerbate the use of categorical distinctions and, correspondingly, the incidence of discrimination (Vallas 2003).

Much of the empirical literature exploring organizational mechanisms of discrimination has focused specifically on how organizational practices mediate the cognitive biases and stereotypes of actors (Baron & Pfeffer 1994). Indeed, Reskin (2000) argues that “the proximate cause of most discrimination is whether and how personnel practices in work organizations constrain the biasing effects of… automatic cognitive processes” (p. 320). Petersen & Saporta (2004) take a bolder stance, starting with the assumption that “discrimination is widespread, and employers discriminate if they can get away with it” (p. 856). Rather than asking why employers discriminate, then, these authors look to the “opportunity structure for discrimination” (in their case, features of job ladders within organizations) that allow or inhibit the expression of discriminatory tendencies (pp. 855–56).

In the following discussion, we briefly consider several important themes relevant to the literature on organizational mechanisms of discrimination. In particular, we examine how organizational structure and practices influence the cognitive and social psychological processes of decision makers (the role of formalized organizational procedures and diversity initiatives), how organizational practices create disparate outcomes that may be independent of decision makers (the role of networks), and how organizations respond to their broader environment.

The role of formalization

One important debate in this literature focuses on the degree to which formalized organizational procedures can mitigate discrimination by limiting individual discretion. The case of the military (Moskos & Butler 1996), for example, and the public sector more generally (DiPrete & Soule 1986, Moulton 1990) provide examples in which highly rationalized systems of hiring, promotion, and remuneration are associated with an increasing representation of minorities, greater racial diversity in positions of authority, and a smaller racial wage gap. Likewise, in the private sector, formal and systematic protocols for personnel management decisions are associated with increases in the representation of racial minorities (Reskin et al. 1999, Szafran 1982, Mittman 1992), and the use of concrete performance indicators and formalized evaluation systems has been associated with reductions in racial bias in performance evaluations (Krieger 1995, Reskin 2000).

Individual discretion has been associated with the incidence of discrimination in credit markets as well. For example, Squires (1994) finds that credit history irregularities on policy applications were often selectively overlooked in the case of white applicants. Conversely, Gates et al. (2002) report that the use of automated underwriting systems (removing lender discretion) was associated with a nearly 30% increase in the approval rate for minority and low-income clients and at the same time more accurately predicted default than traditional methods. These findings suggest that formalized procedures can help to reduce racial bias in ways that are consistent with goals of organizational efficiency.

At the same time, increased bureaucratization does not necessarily mitigate discriminatory effects. According to Bielby (2000), rules and procedures are themselves subject to the influence of groups inside and outside the organization who “mobilize resources in a way that advances their interests,” with competition between groups potentially undermining the neutrality of bureaucratic procedures (Bielby 2000, p. 123; see also Ross & Yinger 2002, Acker 1989). Additionally, there is evidence that formalized criteria are often selectively enforced, with greater flexibility or leeway applied in the case of majority groups (Wilson et al. 1999, Squires 1994). Likewise, indications of racial bias in performance evaluations cast doubt on the degree to which even formalized assessments of work quality can escape the influence of race (McKay & McDaniel 2006). The degree to which formalization can reduce or eliminate discrimination, thus, remains open to debate, with effects depending on the specific context of implementation.

Diversity initiatives

Since the passage of Title VII in the 1964 Civil Rights Act, most large organizations have taken active steps to signal compliance with antidiscrimination laws. Deliberate organizational efforts to address issues of discrimination (or the perception thereof), either in disparate treatment or disparate impact, often are labeled as diversity initiatives, and these practices are widespread. Winterle (1992) cites a 1991 survey of organizations demonstrating that roughly two-thirds provided diversity training for managers, half provided a statement on diversity from top management, and roughly one-third provided diversity training for employees and/or had a diversity task force (see also Wheeler 1995, Edelman et al. 2001). Not all such initiatives, however, have any proven relationship to actual diversity outcomes. Kalev et al. (2006) examine the efficacy of active organizational efforts to promote diversity, focusing specifically on three of the most common organizational practices: the implementation of organizational accountability by creating new positions or taskforces designed specifically to address diversity issues, managerial bias training, and mentoring and network practices. They find that practices designed to increase organizational authority and accountability are the most effective in increasing the number of women and minorities in management positions. Networking and mentoring programs appear somewhat useful, whereas programs focused on reducing bias (e.g., diversity training) have little effect. These results suggest that organizational initiatives to reduce racial disparities can be effective, but primarily when implemented with concrete goals to which organizational leadership is held accountable.7

Taking a broader look at race-targeted employment policies, Holzer & Neumark (2000) investigate the effects of affirmative action on the recruitment and employment of minorities and women. They find that affirmative action is associated with increases in the number of recruitment and screening practices used by employers, increases in the number of minority applicants and employees, and increases in employers’ tendencies to provide training and formal evaluations of employees. Although the use of affirmative action in hiring is associated with somewhat weaker credentials among minority hires, actual job performance appears unaffected.

The role of networks

In addition to examining how organizational policies and practices shape the behavior of decision makers and gatekeepers, researchers must acknowledge that some mechanisms relevant to the perpetuation of categorical inequality might operate independently of the actions of individuals. Indeed, many organizational policies or procedures can impose disparate impact along racial lines with little direct influence from individual decision makers. The case of networks represents one important example. The role of networks in hiring practices is extremely well documented, with networks generally viewed as an efficient strategy for matching workers to employers with advantages for both job seekers (e.g., Granovetter 1995) and employers (e.g., Fernandez et al. 2000). At the same time, given high levels of social segregation (e.g., McPherson et al. 2001), the use of referrals is likely to reproduce the existing racial composition of the company and to exclude members of those groups not already well represented (Braddock & McPartland 1987). In an analysis of noncollege jobs, controlling for spatial segregation, occupational segregation, city, and firm size, Mouw (2002) finds that the use of employee referrals in predominantly white firms reduces the probability of a black hire by nearly 75% relative to the use of newspaper ads.8Petersen et al. (2000) using data on a high-technology organization over a 10-year period find that race differences in hiring are eliminated when the method of referral is considered, suggesting that the impact of social networks on hiring outcomes is strong and may be more important than any direct action taken by organization members. Irrespective of an employer’s personal racial attitudes, the use of employee referrals is likely to reproduce the existing racial composition of an organization, restricting valuable employment opportunities from excluded groups (see also Royster 2003, Waldinger & Lichter 2003).

Networks and network composition may matter not only for the purposes of obtaining information and referrals for jobs, but also within jobs for the purposes of informal mentoring, contacts, and relevant information important to advancement (Ibarra 1993, Grodsky & Pager 2001). Mechanisms of homosocial reproduction, or informal preferences for members of one’s own group, can lead to network configurations of informal mentorship and sponsorship that contribute to the preservation of existing status hierarchies (Kanter 1977; see also Elliot & Smith 2001, Sturm 2001). The wide-ranging economic consequences that follow from segregated social networks corresponds to what Loury (2001, p. 452) refers to as the move from “discrimination in contract” to “discrimination in contact.” According to Loury, whereas earlier forms of discrimination primarily reflected explicit differences in the treatment of racial groups, contemporary forms of discrimination are more likely to be perpetuated through informal networks of opportunity that, though ostensibly race-neutral, systematically disadvantage members of historically excluded groups.

Organizations in context

Much of the research discussed above considers the organization as a context in which decisions and procedures that affect discriminatory treatment are shaped. But organizations themselves are likewise situated within a larger context, with prevailing economic, legal, and social environments conditioning organizational responses (Reskin 2003). When labor markets expand or contract, organizations shift their recruitment and termination/retention strategies in ways that adapt to these broader forces (e.g., Freeman & Rodgers 1999). When antidiscrimination laws are passed or amended, organizations respond in ways that signal compliance (Dobbin et al. 1993), with the impact of these measures varying according to shifting levels or strategies of government enforcement (Kalev & Dobbin 2006, Leonard 1985). At the same time, organizations are not merely passive recipients of the larger economic and legal context. In the case of the legal environment, for example, organizations play an active role in interpreting and shaping the ways that laws are translated into practice. Edelman (1992), Dobbin et al. (1993), and Dobbin & Sutton (1998) have each demonstrated ways in which the U.S. federal government’s lack of clear guidance regarding compliance with antidiscrimination laws and regulations allowed organizations to establish and legitimate their own compliance measures. According to Edelman (1992, p. 1542), “organizations do not simply ignore or circumvent weak law, but rather construct compliance in a way that, at least in part, fits their interests.” Organizational actors, then, can wind up playing the dual role of both defining and demonstrating compliance, with important implications for the nature, strength, and impact of antidiscrimination laws and likewise for the patterns of discrimination that emerge in these contexts.

Organizations occupy a unique position with respect to shaping patterns of discrimination. They mediate both the cognitive and attitudinal biases of actors within the organization as well as the influence of broader economic and legal pressures applied from beyond. Recognizing the specific features of organizational action that affect patterns of discrimination represents one of the most important contributions of sociological research in this area. To date, the vast majority of organizational research has focused on the context of labor markets; investigations of organizational functioning in other domains (e.g., real estate, retail sales, lending institutions) would do much to further our understanding of how collective policies and practices shape the expression of discrimination.

Structural Factors

The majority of research on discrimination focuses on dynamics between individuals or small groups. It is easiest to conceptualize discrimination in terms of the actions of specific individuals, with the attitudes, prejudices, and biases of majority group members shaping actions toward minority group members. And yet, it is important to recognize that each of these decisions takes place within a broader social context. Members of racial minority groups may be systematically disadvantaged not only by the willful acts of particular individuals, but because the prevailing system of opportunities and constraints favors the success of one group over another. In addition to the organizational factors discussed above, broader structural features of a society can contribute to unequal outcomes through the ordinary functioning of its cultural, economic, and political systems (see also National Research Council 2004, chapter 11). The term structural discrimination has been used loosely in the literature, along with concepts such as institutional discrimination and structural or institutional racism, to refer to the range of policies and practices that contribute to the systematic disadvantage of members of certain groups. In the following discussion, we consider three distinct conceptualizations of structural discrimination, each of which draws our attention to the broader, largely invisible contexts in which group-based inequalities may be structured and reproduced.

A legacy of historical discrimination

This first conceptualization of structural discrimination stands furthest from conventional definitions of discrimination as an active and ongoing form of racial bias. By focusing on the legacies of past discrimination, this emphasis remains agnostic about the relevance of contemporary forms of discrimination that may further heighten or exacerbate existing inequalities. And yet, the emphasis on structural discrimination—as opposed to just inequality— directs our attention to the array of discriminatory actions that brought about present day inequalities. The origins of contemporary racial wealth disparities, for example, have well-established links to historical practices of redlining, housing covenants, racially targeted federal housing policies, and other forms of active discrimination within housing and lending markets (e.g., Massey & Denton 1993). Setting aside evidence of continuing discrimination in each of these domains, these historical practices themselves are sufficient to maintain extraordinarily high levels of wealth inequality through the intergenerational transition of advantage (the ability to invest in good neighborhoods, good schools, college, housing assistance for adult children, etc.) (Oliver & Shapiro 1997). According to Conley (1999), even if we were to eliminate all contemporary forms of discrimination, huge racial wealth disparities would persist, which in turn underlie racial inequalities in schooling, employment, and other social domains (see also Lieberson & Fuguitt 1967). Recent work based on formal modeling suggests that the effects of past discrimination, particularly as mediated by ongoing forms of social segregation, are likely to persist well into the future, even in the absence of ongoing discrimination (see Bowles et al. 2007, Lundberg & Startz 1998).

These historical sources of discrimination may become further relevant, not only in their perpetuation of present-day inequalities, but also through their reinforcement of contemporary forms of stereotypes and discrimination. As in Myrdal’s (1944) “principle of cumulation,” structural disadvantages (e.g., poverty, joblessness, crime) come to be seen as cause, rather than consequence, of persistent racial inequality, justifying and reinforcing negative racial stereotypes (pp. 75–78). Bobo et al. (1997, p. 23) argue that “sharp black-white economic inequality and residential segregation…provide the kernel of truth needed to regularly breathe new life into old stereotypes about putative black proclivities toward involvement in crime, violence, and welfare dependency.” The perpetuation of racial inequality through structural and institutional channels can thus be conducive to reinforcing negative racial stereotypes and shifting blame toward minorities for their own disadvantage (see also Sunstein 1991, p. 32; Fiske et al. 2002).

Contemporary state policies and practices

This second conceptualization of structural discrimination accords more with conventional understandings of the term, placing its emphasis on those contemporary policies and practices that systematically disadvantage certain groups. Paradigmatic cases of structural discrimination include the caste system in India, South Africa under apartheid, or the United States during Jim Crow—each of these representing societies in which the laws and cultural institutions manufactured and enforced systematic inequalities based on group membership. Although the vestiges of Jim Crow have long since disappeared in the contemporary United States, there remain features of American society that may contribute to persistent forms of structural discrimination (see Massey 2007, Feagin 2006).

One example is the provision of public education in the United States. According to Orfield & Lee (2005, p. 18), more than 60% of black and Latino students attend high poverty schools, compared with 30% of Asians and 18% of whites. In addition to funding disparities across these schools, based on local property taxes, the broader resources of schools in poor neighborhoods are substantially limited: Teachers in poor and minority schools are likely to have less experience, shorter tenure, and emergency credentials rather than official teaching certifications (Orfield & Lee 2005).At the same time, schools in high poverty neighborhoods are faced with a greater incidence of social problems, including teen pregnancy, gang involvement, and unstable households (Massey & Denton 1993). With fewer resources, these schools are expected to manage a wider array of student needs. The resulting lower quality of education common in poor and minority school districts places these students at a disadvantage in competing for future opportunities (Massey 2006).

A second relevant example comes from the domain of criminal justice policy. Although evidence of racial discrimination at selective decision points in the criminal justice system is weak (Sampson & Lauritsen 1997), the unprecedented growth of the criminal justice system over the past 30 years has had a vastly disproportionate effect on African Americans.9 Currently, nearly one out of three young black men will spend time in prison during his lifetime, a figure that rises to nearly 60% among young black high school dropouts (Bonczar & Beck 1997, Pettit & Western 2004). Given the wide array of outcomes negatively affected by incarceration—including family formation, housing, employment, political participation, and health—decisions about crime policy, even when race-neutral in content, represent a critical contemporary source of racial disadvantage (Pattillo et al. 2003, Pager 2007b, Manza & Uggen 2006).

These examples point to contexts in which ostensibly race-neutral policies can structure and reinforce existing social inequalities. According to Omi & Winant (1994), “through policies which are explicitly or implicitly racial, state institutions organize and enforce the racial politics of everyday life. For example, they enforce racial (non)discrimination policies, which they administer, arbitrate, and encode in law. They organize racial identities by means of education, family law, and the procedures for punishment, treatment, and surveillance of the criminal, deviant and ill” (p. 83). Even without any willful intent, policies can play an active role in designating the beneficiaries and victims of a particular system of resource allocation, with important implications for enduring racial inequalities.

Accumulation of disadvantage

This third category of structural discrimination draws our attention to how the effects of discrimination in one domain or at one point in time may have consequences for a broader range of outcomes. Through spillover effects across domains, processes of cumulative (dis)advantage across the life course, and feedback effects, the effects of discrimination can intensify and, in some cases, become self-sustaining.

Although traditional measures of discrimination focus on individual decision points (e.g., the decision to hire, to rent, to offer a loan), the effects of these decisions may extend into other relevant domains. Discrimination in credit markets, for example, contributes to higher rates of loan default, with negative implications for minority entrepreneurship, home ownership, and wealth accumulation (Oliver & Shapiro 1997). Discrimination in housing markets contributes to residential segregation, which is associated with concentrated disadvantage (Massey & Denton 1993), poor health outcomes (Williams 2004), and limited educational and employment opportunities (Massey & Fischer 2006, Fernandez & Su 2004

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