Gender, Education and Employment

Chapter 134 examines a central paradox of contemporary social change in Mithila, Vajji and Anga: girls and women have made major gains in schooling and, in Bihar, female enrolment now matches or exceeds male enrolment at several educational levels, yet the conversion of education into secure paid work remains sharply unequal. Education, employment and gender cannot therefore be read as a simple sequence in which more years of schooling automatically produce economic independence. Household care obligations, marriage timing, transport, occupational segregation, public-sector recruitment, migration, caste and class, digital access and the local availability of work all mediate the passage from classroom to labour market. The regional method used throughout this volume remains essential. Bihar, Madhesh Province and the historical-cultural regions do not coincide. UDISE+, AISHE and the Periodic Labour Force Survey describe Indian administrative units using distinct reference populations, while Nepal’s 2021 census, 2022 Demographic and Health Survey, 2022–23 Living Standards Survey and other statistical programmes use different definitions. The chapter therefore uses Bihar and Madhesh as evidence frames without manufacturing a single “Mithila–Vajji–Anga” gender index. Where figures are compared, the denominator, age range and survey concept are stated so that enrolment parity is not confused with literacy, labour-force participation or employment. 134.1 Gender links household reproduction to the wider economy Gender is an economic institution as well as a social identity. Households allocate food, schooling, care, mobility, property, paid work and migration through gendered expectations. Women may cultivate land, manage livestock, care for children and older people, supervise construction, operate accounts and organise ceremonies while being recorded as outside paid employment. Men may migrate and remit earnings while being absent from the daily household economy. Education can change these arrangements by expanding information, credentials and aspirations, but its effects depend on whether women can travel, seek work, retain earnings and negotiate domestic responsibilities. The correct unit of analysis is therefore not the isolated worker or student but the relationship among education, household labour, mobility and income. 134.2 Evidence architecture: enrolment, learning, credentials and labour measures are not interchangeable UDISE+ measures school enrolment and institutional indicators; AISHE measures higher-education institutions and enrolment; PLFS measures labour-force status; NFHS measures selected educational, health, digital and household indicators; censuses provide population structure and literacy; and administrative programme records describe beneficiaries rather than the population as a whole. A girl can be enrolled without attending regularly, can complete secondary school without entering college, can hold a degree while preparing for an examination, and can undertake unpaid family work while being classified outside employment under another reference period. Gender analysis becomes misleading when these stages are collapsed into one “empowerment” number. The chapter therefore treats educational access, educational completion, labour-force participation, work status, earnings and control over income as related but distinct outcomes. 134.3 Literacy change is generational, not instantaneous Literacy rates are stocks built from many past cohorts. Older women who grew up before mass schooling entered the region at very different educational starting points from girls now in primary or secondary HISTORY OF MITHILA, VAJJI & ANGA — VOLUME II school. This is especially visible in Madhesh Province, where the 2021 census reported literacy among people aged five and above at 72.5 percent for males and 54.7 percent for females. That gap is historically important, but it should not be projected unchanged onto current school-age children. In Bihar too, the expansion of girls’ schooling since the 2000s means that younger female cohorts are substantially more educated than their mothers and grandmothers. Contemporary gender history must therefore distinguish cohort replacement from immediate policy change. 134.4 Bihar has reached gender parity in school enrolment ratios before reaching high enrolment at every level UDISE+ 2024–25 shows a striking pattern. In Bihar, girls’ Gross Enrolment Ratio exceeded boys’ at primary, upper-primary, secondary and higher-secondary levels: 78.9 versus 75.7 at primary, 72.2 versus 65.9 at upper primary, 54.8 versus 47.7 at secondary and 40.4 versus 35.9 at higher secondary. The Gender Parity Index is therefore at or above one across these stages. Yet the absolute ratios decline sharply as the level rises. Gender parity and universal participation are different achievements. A system can be relatively equal between boys and girls while still losing large shares of both sexes before higher secondary. The contemporary challenge is thus retention and transition as well as gender parity. 134.5 The secondary and higher-secondary transition remains the critical educational bottleneck The steep fall in Bihar’s GER from primary to secondary and higher secondary shows where educational aspiration encounters practical constraints. Costs rise; schools may be farther away; examination failure becomes more consequential; household labour and wage work compete with study; and marriage discussions may begin for girls in late adolescence. For boys, migration and casual work can also pull students away from school. The gender question is therefore embedded in a broader transition problem. Policies that only count entry into Class I can miss the stage at which education becomes a credential with labour-market value. Safe transport, nearby secondary schools, subject choice, teachers, examination support and affordable post-school pathways become decisive for whether enrolment parity produces completed qualifications. 13791379 GAJENDRA THAKUR Figure 532 — Bihar school GER by sex, 2024–25: girls exceed boys at each shown level, but absolute enrolment ratios fall sharply toward higher secondary. 134.6 The bicycle programme illustrates how mobility can be an education policy Bihar’s long-running cycle programme for schoolgirls became important because it addressed a concrete spatial constraint rather than treating gender inequality only as an attitude. Research on the programme found that reducing the effective cost and risk of travel could raise girls’ secondary-school enrolment. Its broader historical significance lies in the visibility of girls moving independently through public space. A bicycle changes daily time use, expands the radius within which a school is reachable and can alter family expectations about adolescent mobility. The lesson extends beyond one scheme: roads, buses, lighting and safe last-mile transport are part of educational infrastructure. A school seat has limited value when reaching it requires a journey families regard as unsafe or socially unacceptable. 134.7 Toilets, menstrual health and school safety affect attendance as much as formal enrolment Gender parity in registration can coexist with unequal attendance. Adolescent girls may miss school when toilets are unusable, water is unavailable, menstrual materials are unaffordable or privacy is weak. Harassment on the route to school or within crowded transport can change family willingness to allow continued study even when tuition is free. These constraints are difficult to capture in a single administrative indicator because they operate through repeated small absences and through household decisions about risk. The historical shift toward mass girls’ education therefore depends on the quality and social usability of infrastructure, not merely its existence. A functioning toilet, a reliable bus and a responsive grievance system can be as consequential as a new classroom. 134.8 Digital access has become part of educational inequality Smartphones and internet connectivity now shape homework, examination forms, scholarship applications, coaching, job searches and communication with teachers. Yet device access inside a household can be gendered. A phone may technically exist but be controlled by a father, brother or husband; data expenditure may be rationed; and young women may face stricter surveillance of online activity than young men. The pandemic made this distinction especially visible when remote learning depended on devices, electricity and connectivity. Digital inclusion should therefore be measured by effective individual use rather than by household ownership alone. For women seeking employment, the same infrastructure later mediates recruitment notices, digital payments, platform work and access to government services. 134.9 Higher education changes the gender balance of aspiration The expansion of colleges and universities has created a new educational landscape in which young women increasingly remain in formal education beyond school. In the wider study region, institutions in Darbhanga, Muzaffarpur, Bhagalpur, Samastipur, Patna and other centres draw students from rural districts, while Janakpur and other Madhesh towns perform similar functions in Nepal. Higher education can delay marriage, enlarge peer networks and produce credentials for teaching, health, administration, banking and professional services. It can also create a prolonged period of dependency if local graduate jobs are scarce. The social meaning of a degree thus extends beyond immediate earnings: it affects marriage negotiations, migration decisions and the expectation that daughters should have an educational biography comparable to sons. HISTORY OF MITHILA, VAJJI & ANGA — VOLUME II 134.10 Bihar’s female higher-education enrolment now slightly exceeds male enrolment AISHE 2023–24 estimated about 14.0 lakh female students and 13.6 lakh male students in higher education in Bihar, placing the state among those where female enrolment exceeded male enrolment. This is a major historical reversal from the period when higher education was overwhelmingly male. The figure does not mean that every district, caste, class or discipline has reached equality, nor does it show completion or employment after graduation. But it demonstrates that the problem can no longer be described simply as the exclusion of women from college. The central question has shifted toward what women study, whether institutions are accessible and safe, and how credentials translate into employment, income and professional authority. Figure 533 — AISHE 2023–24 estimated higher-education enrolment in Bihar: female enrolment (14.0 lakh) slightly exceeded male enrolment (13.6 lakh). 134.11 Discipline choice and occupational segregation begin before the first job Equal numbers in higher education do not imply equal fields of study. Social expectations, school preparation, entrance examinations, hostel availability and perceived job security influence whether women enter arts, teacher education, nursing, medicine, science, engineering, law or commerce. Families may prefer courses that are available near home or lead to occupations considered compatible with marriage and care. Men may be more readily permitted to migrate for engineering, technical training or private-sector work. This sorting matters because disciplines have different earnings distributions and recruitment channels. Gender segregation in the labour market is therefore partly produced inside the education system. Expanding women’s access to laboratories, technical institutes, professional colleges and internships is not a separate agenda from employment policy. 13811381 GAJENDRA THAKUR 134.12 Local universities reduce mobility barriers but can also reproduce labour- market queues A dense network of colleges allows women to study without leaving the district, which can be decisive where residential migration is expensive or socially constrained. At the same time, local access can concentrate students in general degrees for which the number of stable salaried jobs grows more slowly than enrolment. The result may be a queue for teaching, clerical, banking and government posts, with years spent in coaching and repeated examinations. This is not educational failure in a simple sense: degrees still carry social value and can improve capabilities. But when employment creation lags behind credential expansion, families may experience a mismatch between the cost of education and the expected return. Gendered restrictions on geographic mobility can make that mismatch sharper for women. 134.13 Coaching migration and competitive examinations produce a new gender geography Competitive examinations have become a major bridge between education and desired employment. Students move temporarily to Patna, Delhi, Kota and other centres, or use online coaching from home. Women’s participation depends on hostel safety, family permission, travel costs and whether extended preparation can be reconciled with marriage expectations. A young man may be allowed several years of uncertain preparation or migration, while a similarly qualified woman may face a shorter household timetable. Digital coaching can reduce some mobility costs but cannot eliminate unequal access to quiet study space, devices and time. The examination economy therefore reveals how gender operates through time as well as space: who is allowed to wait for a preferred job, and for how long. 134.14 Madhesh retains a large female educational deficit among adult cohorts Nepal’s 2021 census and 2022 DHS show that women in Madhesh remain educationally disadvantaged relative to men and to women in several other provinces. The census recorded a female literacy rate of 54.7 percent among people aged five and above, compared with 72.5 percent for males. The 2022 DHS reported that 46 percent of women aged 15–49 in Madhesh had no education, 29 percent had some basic education, 23 percent some secondary education and only 2 percent more than secondary education. These measures use different age ranges and concepts, but together they show that the educational transition is incomplete. Younger cohorts may improve faster than the adult average, so policy needs both school retention for girls and second-chance learning for adult women. 134.15 Cross-border educational comparison requires denominator discipline Bihar’s school GER, AISHE enrolment, Madhesh census literacy and DHS educational attainment cannot be placed on one ladder as if they were the same variable. GER can exceed 100 because of age-grade mismatch; literacy is a population characteristic; attainment describes completed or attended levels; and higher-education enrolment counts students in institutions. The temptation to create a single cross-border score should be resisted. A stronger regional history compares processes: expansion of schooling, persistence of adult female illiteracy, growth of college attendance, mobility to educational centres and the uneven translation of credentials into work. The shared pattern is not identical numerical performance but the coexistence of rapid educational change with deep household and labour-market constraints. HISTORY OF MITHILA, VAJJI & ANGA — VOLUME II 134.16 Labour-force participation reveals the limits of an education-only account of gender change The Periodic Labour Force Survey Annual Report 2025 estimated Bihar’s usual-status labour-force participation rate for people aged fifteen and above at 75.7 percent for males and 24.7 percent for females. The female rate was 26.1 percent in rural areas and 13.9 percent in urban areas. These are state-level measures, not specific to Mithila, Vajji or Anga, but they establish the scale of the gender gap in the labour market. The contrast with school and higher-education parity is analytically important. More women are studying, yet a much smaller share of adult women are counted in the labour force. Education is necessary for many occupations, but the supply of credentials alone does not determine labour-force entry. 134.17 The urban female participation gap is not evidence that rural women are necessarily more economically empowered Bihar’s 2025 female LFPR was higher in rural than urban areas. That difference should not be interpreted mechanically as greater rural empowerment. Rural women may enter the labour force through cultivation, livestock, casual work or unpaid family enterprises when household survival requires it, while urban households may withdraw women from low-status work as income rises or while women wait for salaried jobs. Conversely, urban women with professional employment may have higher earnings and autonomy despite the lower aggregate participation rate. Labour-force participation measures whether someone is working or seeking work under a defined status; it does not directly measure job quality, earnings, ownership or bargaining power. Gender analysis therefore needs both participation and the character of work. Figure 534 — Bihar PLFS 2025 labour-force participation, age 15+: a large male–female gap persists in both rural and urban areas despite educational gains. 134.18 Unpaid family work and care complicate the boundary between “working” and “not working” Women’s economic contribution is especially vulnerable to under-recognition where production is organised through households. Feeding livestock, processing grain, transplanting, sorting produce, maintaining kitchen gardens, collecting fuel, supervising hired labour or helping in a shop may be reported 13831383 GAJENDRA THAKUR differently depending on the survey question and respondent. Care work adds another layer: cooking, cleaning, childcare, elder care and support for migrants reproduce the labour force without usually appearing as paid employment. Time-use evidence from India has repeatedly shown that women perform much more unpaid domestic and care work than men. The policy implication is not to classify every domestic task as employment, but to recognise that unpaid responsibilities shape whether women have time, mobility and continuity for paid work. 134.19 The “education–employment paradox” is produced by job preferences, constraints and labour demand together It is tempting to explain low female employment either as conservative family culture or as a shortage of jobs. Both explanations are incomplete on their own. Education can raise the reservation wage: a graduate may reject agricultural or domestic service work while waiting for teaching, banking or government recruitment. Families may permit work considered secure and respectable but oppose night shifts, distant factories or irregular service jobs. Employers may discriminate or fail to provide safe transport, toilets and maternity support. Local economies may simply generate too few formal positions. The resulting low participation is therefore an equilibrium produced by aspirations, norms, care burdens, safety, wages and labour demand. Policy must act on several margins simultaneously. 134.20 Marriage and motherhood change the timing of employment even when education is retained Chapter 133 showed that marriage is becoming later and more negotiated, but it remains a major transition in women’s residence and responsibilities. A woman may complete college and work before marriage, then stop after moving to a village with fewer jobs or after childbirth. Others may enter teaching, health work or self-employment only after children are older. Employment statistics observed at one date can therefore miss life-course movement in and out of work. Affordable childcare, maternity protection, flexible transport and the possibility of returning to employment after a break are essential if educational investment is to retain economic value over the life course. The relevant question is not only whether women ever work, but whether they can sustain and re-enter work across family transitions. 134.21 Male migration can enlarge women’s responsibilities without automatically enlarging women’s rights Migration is one of the central institutions of the regional economy. When men work in Delhi, Punjab, Gujarat, the Gulf, Kathmandu or elsewhere, women who remain may manage farming, schooling, remittances, debt payments and relations with local government. This can increase practical decision-making and public visibility. Yet land titles, bank control and major investment decisions may still remain with absent men or senior relatives. “Feminisation of agriculture” or household management therefore does not automatically mean female ownership or bargaining power. Education can help women navigate banks, digital payments and administrative systems, but durable economic agency also depends on property rights, documentation and recognition of women as farmers, entrepreneurs and account holders in their own right. 134.22 Public-sector employment remains disproportionately important to educated women’s aspirations Teaching, health services, banking, administration, policing and other government-linked occupations carry a combination of salary, status, predictable hours and perceived security that many families regard as HISTORY OF MITHILA, VAJJI & ANGA — VOLUME II compatible with women’s employment. This helps explain the social intensity of competitive examinations and teacher recruitment. Public employment can create visible female role models and establish norms of women travelling to workplaces and handling official authority. But the number of applicants often far exceeds vacancies, producing long waiting periods and repeated examination cycles. A development strategy cannot rely on government jobs alone. The challenge is to make private and self-employment sufficiently safe, remunerative and socially legitimate that educated women do not face a binary choice between a scarce public post and economic inactivity. 134.23 Health, education and care services are both employment sectors and social infrastructure The expansion of schools, anganwadi centres, health facilities, community programmes and private clinics has created large fields of female employment. Teachers, nurses, auxiliary health workers, community mobilisers and childcare workers connect paid or honorarium work with services used by other women. This produces a multiplier effect: a woman employed in health or education earns income, while the service she provides can reduce another household’s care burden or improve girls’ schooling. Yet many frontline roles remain low-paid, contractual or classified as volunteer/honorarium work. Gender-sensitive employment policy must therefore examine job quality inside sectors stereotyped as “women’s work”. Social value does not automatically generate adequate wages, pension coverage or promotion opportunities. 134.24 Women’s collectives and JEEViKA shift economic participation from the individual to the group Self-help groups have become one of Bihar’s most important institutional routes for women’s financial inclusion and collective action. JEEViKA and related programmes organise savings, credit, livelihoods, producer activity and links to banks and public schemes through village-level women’s groups. Their economic significance extends beyond microcredit. Regular meetings create public participation, accounting experience, peer networks and a platform through which women can negotiate with banks or local officials. The limitation is equally important: group membership is not the same as profitable enterprise, and debt- financed activity can fail when markets are weak. Collective institutions work best when credit is connected to skills, procurement, storage, transport, insurance and reliable demand rather than treated as a substitute for broader employment creation. 134.25 Self-employment and platform work expand opportunity but transfer risk to workers Digital payments, social media and e-commerce allow some women to sell food, tailoring, tuition, beauty services, craft products or agricultural goods without entering a conventional workplace. Home-based enterprise can fit care obligations and reduce travel barriers. It can also reproduce low scale, irregular earnings and dependence on family labour. Platform work adds another possibility through delivery, online services and digital marketplaces, but the infrastructure and occupational mix remain strongly gendered. Access to a smartphone, bank account and digital literacy is necessary but not sufficient. Women need working capital, market information, safe mobility, grievance mechanisms and social protection. Enterprise should be evaluated through net income and control over earnings, not by the number of accounts or registrations created. 13851385 GAJENDRA THAKUR 134.26 Informality keeps employment, social protection and identity documents tightly connected Much of the regional labour market is informal: casual construction, agricultural work, domestic service, petty trade, transport-linked services, home production and small enterprises. Informal workers can move between occupations and locations without stable contracts. For women, irregular work often combines with interrupted labour-force participation and weak documentary proof of earnings. Portability of ration benefits, health coverage, maternity entitlements, pensions and worker registration therefore matters. The growth of digital public infrastructure can improve access, but it can also exclude women whose phone, biometric or bank access is mediated by another household member. Social protection becomes part of employment policy when the labour market cannot guarantee stable employer-provided benefits. 134.27 Caste, class, religion and location mediate the meaning of gender parity Aggregate female averages conceal large differences. Landholding households, Dalit labouring households, Muslim artisan or trading households, urban salaried families and migrant-dependent villages face different combinations of work opportunity and social constraint. A college degree may open salaried employment for one woman while another equally educated woman lacks transport, networks or permission to migrate. Poor women may have high work participation because they cannot afford withdrawal from labour, yet remain concentrated in low-paid work. Wealthier women may have low measured participation but greater property and educational resources. Gender inequality is therefore intersectional in a literal economic sense: it is produced through the interaction of gender with assets, caste/community position, geography, occupation and family structure. Figure 535 — From school access to economic agency: credentials must pass through mobility, job availability, care arrangements and social institutions before they become income and bargaining power. 134.28 Madhesh shows the same conversion problem under a different statistical and institutional system Nepal’s recent evidence reinforces the need to separate education from employment. The Nepal Living Standards Survey IV, 2022–23, reported a national female labour-force participation rate far below the male rate and identified Madhesh as the province with the largest sex gap: 54.9 percent for males and 16.5 percent HISTORY OF MITHILA, VAJJI & ANGA — VOLUME II for females among the relevant working-age population in its sex-disaggregated provincial analysis. At the same time, the 2021 census and 2022 DHS document large female educational deficits in Madhesh adult cohorts. The fourth Nepal Labour Force Survey was still being fielded/reviewed in 2026, so it would be wrong to invent newer completed labour-force results. The cross-border pattern is comparable analytically, not statistically identical. 134.29 Measurement discipline is essential: GPI, GER, LFPR, WPR and earnings answer different questions A Gender Parity Index near one says girls and boys have similar enrolment ratios; it does not say enrolment is high. GER measures enrolment relative to the official age-group population and may include over-age or under-age students. LFPR measures the share working or seeking work; WPR measures the share actually working; unemployment is calculated within the labour force rather than the whole population. Earnings and job quality require still other data. Census literacy uses a different age threshold from school indicators. These distinctions are not technical footnotes but the basis of sound historical interpretation. The central contemporary finding is precisely that indicators can move in different directions: educational parity can improve while adult female labour participation remains low. 134.30 Conclusion: the next transition is from educational presence to economic agency The most important gender transformation of the past generation has been the normalisation of girls’ and women’s educational presence. Bihar’s 2024–25 school data show parity or a female advantage in enrolment ratios, and AISHE 2023–24 shows female higher-education enrolment slightly above male enrolment. Yet PLFS 2025 records a large labour-force gap, while Madhesh evidence shows both an adult educational deficit and especially low female labour-force participation. The next phase of social change therefore cannot be measured only by getting girls into classrooms. It requires safe mobility, completion, skills, diverse jobs, childcare, property and financial control, social protection and the right to remain employed across marriage and motherhood. Education becomes transformative when women can convert credentials into choices, income and durable authority over their own economic lives. Table 134.1 — Evidence architecture for analysing gender, education and employment Evidence source What it establishes Use in Chapter 134 Main limitation UDISE+ 2024–25 school GER and GPI by sex shows Bihar gender enrolment is not and level parity alongside completion, learning falling enrolment at or employment higher levels AISHE 2023–24 higher-education enrolment shows female institutional by sex and institution enrolment slightly enrolment; not above male graduate enrolment in Bihar employment PLFS Annual Report 2025 LFPR/WPR/unemployment measures state level; definitions by sex, age and rural–urban contemporary Bihar differ from census location labour-market gender and surveys gap Census of India 2011 literacy, work and long baseline for dated; no completed population structure district-level gender post-2011 census yet reconstruction NFHS-5 and NFHS-6 education, marriage, digital links education with sample surveys; Bihar and household indicators for life-course and indicators do not defined cohorts household conditions equal labour-force 13871387 GAJENDRA THAKUR Evidence source What it establishes Use in Chapter 134 Main limitation statistics Nepal NPHC 2021, sex-disaggregated literacy and adult educational census categories Madhesh report population structure gender gap in differ from Indian Madhesh education statistics Nepal DHS 2022 women’s educational shows incomplete women 15–49; not a attainment and life-course female educational labour-force survey indicators transition in Madhesh Nepal Living Standards labour-market indicators by documents very low survey definitions Survey IV 2022–23 sex and province female participation and reference in Madhesh population differ from PLFS Programme/administrative beneficiaries, SHGs, explains institutional coverage is records scholarships, transport and mechanisms behind programme-specific, service delivery change not population representative Qualitative and time-use care work, norms, mobility, explains why similar context-specific; not research job preferences and credentials can a substitute for household bargaining produce different representative outcomes estimates