Shaping de Facto Brain Drain A qualitative Enquiry of Push and Pull Factors of Emigration among Algerian Physicians Working Abroad
Bibliographic record
Abstract
The aim of this research was to understand the different push and pull factors of physicians’ emigration from Algeria and how they perceived and experienced these factors. A qualitative analysis was conducted with actual emigrants to different countries. The findings were analyzed using a content analysis. A total of eight generalists medical-surgical and medical agreed to take part in this study. The participants were emigrants to the USA, the UK, France, Germany, Canada and the Middle East. Almost all participants agreed that the main drivers of emigration are: working conditions, personal motives and socio-economic factors for both the source and receiving country. Most participants perceive push factors as a source of fear and consider them as imprisonment that poses increased pressure, while pull factors are perceived as an alternative to emancipating from constraint in home country. The push and pull framework is significant in understanding different factors of emigration. Policy-makers need to make efforts to bridge the lacuna between donor and host countries and to reverse these losses into brain gain through in-depth reforms.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".