The Nexus between Female Labour Force Participation (FLFP) and Fertility rate in Selected ASEAN Countries: Panel Cointegration Approach
Bibliographic record
Abstract
The principal objective of this paper is to investigate the dilemma between the female labour force participation rate and total fertility rate for the ASEAN-6 countries from the period 1995 to 2013 using panel cointegration and long-run structural estimation. The cointegration results confirm that the female labour force participation rate and total fertility rate are cointegrated for the panel of ASEAN-6 countries. Whereas, long-run Granger causality authenticate the causality run from the total fertility rate to the female labour force participation rate. Moreover, the results show that 1percent increase in the total fertility rate cause in a 0.44 percent decrease in the female labour force participation rate for the ASEAN-6 countries. The TFR highest negative effect observed in Indonesia and smallest observed in Thailand. The results of fully modify ordinary least square confirm the long run panel relationship between female labour force and total fertility rate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".