Through a gender lens: explaining North‐Eastern Thai women’s participation in adult literacy education
Bibliographic record
Abstract
This ethnographic study employs a gender perspective to understand the motivations of eight women literacy learners participating in a village‐based functional literacy programme in rural North‐eastern Thailand. Field research took place over six months of periodic residence in a North‐eastern Thai village, and involved participant observation, individual interviews and informal focus groups. An analysis of the women’s reproductive, productive and community roles, and their practical and strategic gender needs (Moser ) is used to frame findings on the women’s participation in the literacy programme. In brief, although the women valued educational programmes that reduced the burden of their reproductive labour, offered income‐generating opportunities in their productive roles and supported their leadership roles in the community, the village literacy programme had limited effect in addressing these practical gender needs. However, because a patriarchal ideology and Buddhist institutions had denied the women access to schooling as children, they now saw the literacy programme as both a symbolic return to school and a collective women’s space to advocate for more desirable adult educational programmes. In these ways, the programme addressed their strategic gender needs. The study argues that a gender lens is critical in explaining women’s participation in literacy programmes and in designing literacy education for development.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".