Analysis of Pull-Factor Determinants of Filipino International Migration
Bibliographic record
Abstract
This paper was conducted to examine the pull-factor determinants of Filipino international migration. This study employed Ordinary Least Square (OLS) estimation of gravity model using panel data consisting of 27 countries of destinations from 2007 to 2011. Results of the study revealed that migration flow over the years is increasing. Furthermore, 39% of Filipino migrants were located in USA, this is followed by Canada, UK, Australia and Italy which is the home of 34%, 15%, 5% and 3% of Filipinos respectively. Estimation results of the determinants of Filipino international migration showed that GDP, unemployment rate, cost of living, fiscal freedom, religion, distance and being a member of OECD are not significant pull factor indicators of Filipino migration. Furthermore, it revealed that Filipino migration is significantly and positively affected by population in the destination country. It shows the higher expectancy of migrants to acquire jobs in the destination country. Moreover, Filipino migrants preferred to migrate to a country which has less corruption and that English speaking countries are preferred destination by Filipino migrants.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".