Empowerment & Gender Equality Among Tribal Women
Bibliographic record
Abstract
Empowerment and gender equality are crucial for the socio-economic development of any community, especially the tribal communities in India. Tribal women face multiple challenges such as low literacy, poor health, lack of access to productive resources, and violence. They also have limited participation in decision-making and political processes, despite their significant role in collecting and managing minor forest produce. To address these issues, various policies and measures have been taken at the national, state, and local levels, but there are still gaps between policy and practice. The patriarchal structure of the society and the household hinders the empowerment of tribal women and their agency. Therefore, there is a need for affirmative action and equitable progress to ensure that tribal women have equal opportunities and rights in all spheres of life. This paper reviews the existing literature on the status and role of tribal women in India, the nature and dimensions of change in their lives, and the challenges and prospects for their empowerment and gender development. The paper also suggests some recommendations for enhancing the empowerment and gender equality of tribal women in India.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".