Does Information Improve the Experience of Pursuing Labor Migration? Evidence from a Field Experiment in Pakistan
Bibliographic record
Abstract
A large literature on international labor migration explores how to improve lowskilled migrants' experience of pursuing and obtaining overseas employment. Much of this scholarship focuses on describing and mitigating difficult, and sometimes exploitative, conditions in the host country. Scholars have paid less attention to factors in home countries that may affect aspiring migrants' experience of looking for overseas work. We help address this gap by conducting a field experiment in the high out-migration country of Pakistan to examine whether receiving new information about employment brokers and overseas opportunities improves aspiring migrants' subjective and objective experience of the job-seeking process. After analyzing the effects of information on those who lack alternative sources of information, we report mixed findings. These highlight the need to think carefully about ways to improve aspiring migrants’ job-seeking experiences, especially with regard to the common assumption that if low-skilled migrants simply “knew more”— that is, had more relevant and accurate information — they would not allow themselves to have negative migration experiences; our findings suggest this is not necessarily always the case.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".