Women empowerment issues – Jobs,Reservation and education

Indian women are working more. Here’s why


From UPSC perspective, the following things are important :

Prelims level : Deendayal Antyodaya Yojana National Rural Livelihood Mission

Mains level : The rise in the Female Labor Force Participation Rate (FLFPR) in rural India

Female Labour Force Participation - Current Affairs

Central Idea:

The rise in the Female Labor Force Participation Rate (FLFPR) in rural India, particularly over the last six years, can be attributed to strategic interventions like the Deendayal Antyodaya Yojana National Rural Livelihood Mission (DAY-NRLM) and the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS). These programs, focusing on skilling support, credit access, and diversified livelihoods for women, have significantly contributed to the economic empowerment of women in rural areas.


Key Highlights:

  • The FLFPR in rural areas increased from 24.6% (2017-18) to 41.5% (2022-23).
  • DAY-NRLM, with over 90 lakh Women’s Self-Help Groups (SHGs), has played a crucial role in transforming the lives of over 9.96 crore women.
  • MGNREGS, providing 260 crore person-days of work annually, has emphasized individual beneficiary schemes, raising incomes for women.
  • Initiatives like MKSP and SVEP under DAY-NRLM have empowered women in agriculture and entrepreneurship, respectively.
  • Social capital of women’s collectives, supported by elected Panchayat leaders, has been instrumental in the success of these programs.


Key Challenges:

  • Despite progress, there’s a need for a more comprehensive understanding of the factors contributing to the increased FLFPR.
  • Low wages under MGNREGS pose a challenge, with men often opting for higher-paying jobs in the market.
  • The article hints at the need for a more detailed analysis of the impact of these programs on the overall socio-economic landscape.


Key Terms:

  • FLFPR: Female Labor Force Participation Rate.
  • DAY-NRLM: Deendayal Antyodaya Yojana National Rural Livelihood Mission.
  • MGNREGS: Mahatma Gandhi National Rural Employment Guarantee Scheme.
  • SHGs: Self-Help Groups.
  • MKSP: Mahila Kisan Sashaktikaran Pariyojana.
  • SVEP: Start-Up Village Entrepreneurship Programme.


Key Phrases:

  • “Skilling support and credit access for diversified livelihoods.”
  • “Low NPAs and the success of social capital.”
  • “Person-days of work generated annually under MGNREGS.”


Key Quotes:

  • “The rise in rural female FLFPR has been accompanied by a rise in the share of self-employment and agriculture among working women.”
  • “The social capital of women’s collectives has transformed the rural scenario.”


Key Statements:

  • “The DAY-NRLM and MGNREGS play a crucial role in improving the female labor force participation rate.”
  • “Raising MGNREGS wage rates, along with increased productivity, is crucial for securing lives of dignity for the poor.”


Key Examples and References:

  • Evaluation studies by the Institute of Rural Management, Anand and Stanford University team.
  • Banking correspondents from DAY-NRLM making digital payments possible.
  • Quality Council of India’s evaluation of SVEP.


Key Facts and Data:

  • FLFPR in rural areas increased from 24.6% (2017-18) to 41.5% (2022-23).
  • DAY-NRLM covers 9.96 crore women, with over 90 lakh SHGs accessing Rs 38,892 crore.
  • MGNREGS generates over 260 crore person-days of work annually.


Critical Analysis:

  • The article provides a detailed account of the initiatives and their impact but lacks a comprehensive analysis of the challenges and potential drawbacks of these programs.
  • The need for a more nuanced understanding of the interplay of factors contributing to increased FLFPR is highlighted but not thoroughly explored.


Way Forward:

  • The government should continue and possibly expand successful initiatives like DAY-NRLM and MGNREGS.
  • Address the challenge of low wages under MGNREGS to attract more workers.
  • Conduct further research to understand the broader socio-economic implications of these programs and refine them accordingly.

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