Indonesian Women’s Struggle Towards Transformation: A Case from ‘Rusunawa’ Community
Bibliographic record
Abstract
This article discusses roles of women in struggling transformation within their community. As one of governmental policies in 2015 about eradication of slum areas under BasukiTjahajaPurnama (‘Ahok’) as previous governor of Jakarta, many flats were built and provided to those who became the target of that program. It’s called ‘Rusunawa’—low cost simple flat. Researchers choose ‘Rusunawa’ Pulogebang (the first flat located on East Jakarta) as the locus of research. Unfortunately, there are new social problems emerge. One of them is adaptation matter: changing habits from previous location to new situation. Crashed by new system—such as paying room regularly every month meanwhile having no permanent job/work yet—occurs seriously impact until now. Besides that, losing home also keep them traumatic. In such situation, not all people can change their way of life rapidly till some women—driven by awareness—striving for changing the community decisively by various sustainable efforts. Therefore, this qualitative research will analyze the three main ideas in Feminist Standpoint Theory: knowledge, experience and power relation. Intrinsic case study is used to get in-depth inquiry. Also, researchers conduct as participant observers and in-depth interviewers towards key informants and community itself. Finally, based on critical paradigm, the results show that those women succeed to lead the community towards social transformation in health, education, economic, and leadership fields.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".