Exploring the Glass Ceiling and Sticky Floor in Malaysia
Bibliographic record
Abstract
Usage of quantile regression is preferred nowadays to examine the gender earnings differentials across the earnings distribution. Based on Household Income Survey of 2009 and 2012, this paper examines the issue in Malaysia. The objective of this study is to evaluate the extent of gender earnings differentials across the earnings distribution in 2009 and 2012, whether the glass ceiling or sticky floor exists in the labour market in Malaysia. Based on the pooled quantile regression analysis, the established results indicate that the earnings gap is increasingly larger towards the bottom of the earnings distribution, a finding that is consistent with the existence of sticky floor in both years. Besides, the gender earnings gap is also accelerating between 75th to 90th percentiles, reflecting that the glass ceiling also prevails at the top of the earnings distribution in both years. Furthermore, it is noted that the impact of sticky floor is greater than glass ceiling. Nonetheless, further findings denote that the extent of sticky floor had been reduced whilst glass ceiling had increased within the period.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".