IMPLEMENTASI AFFIRMATIVE ACTION KUOTA PEREMPUAN DALAM PARTAI POLITIK DAN LEMBAGA PERWAKILAN RAKYAT DAERAH (Studi di Wilayah Kota Malang)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the 2009 legislative general election, there were 793 definitive candidates, consisting of 528 men and 265 women. Therefore, the average percentage of definitive female candidates from the whole parties was 33% and in general it seems that the percentage was above 30%. But, an affirmative action as stated on the law on the election of the house of representative members in Malang city in 2009 was not reached, since the number of the elected female legislative representative was still under quota of 30%. Factors causing such less optimum affirmative action in political parties and the house of representative in Malang city are as follows: (1) the political context dominated by men so that the women’s interest was less accommodated. (2) the social context dominated by men so this resulted in masculine practices and (3) the cultural context dominated by a patriarchal tradition resulting a social construction on the division of men and women, and the legal factor through the decision of the constitutional court that did not condition the legislative candidates based on the highest voters, instead of the number order. Kata Kunci: affirmative action, perempuan, partai politik, lembaga perwakilan rakyat daerah
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it