The ARDL Test of Gender Kuznets Curve for G7 Countries
Bibliographic record
Abstract
The Gender Kuznets Curve (GKC) hypothesis argues that economic development has a non-linear effect on the female share of workers. There is, however, growing debate on the exact shape of this non-linear relationship. The aim of this paper is to test the GKC hypothesis in order to determine whether data supports a quadratic or a cubic GKC for each G7 countries in the long run. The ARDL bounds testing approach of cointegration yields evidence for the following: Canada, United Kingdom and United States have an inverted U-shaped GKC; Japan has an S-shaped GKC and France has an inverted-S shaped GKC; and finally that Italy and Germany have no long run GKC relationship in the respective periods of countries considered. We conclude that gender equality is not a direct result of development, and therefore policy makers having a gender equalization policy need to subsidize the employment of female workers in periods of fall.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".