Effects of the COVID‐19 pandemic on the Colombian labour market: Disentangling the effect of sector‐specific mobility restrictions
Bibliographic record
Abstract
We assess the effect of the COVID-19 pandemic and particularly the sector-specific mobility restrictions on the Colombian labour market. We exploit the sectoral and temporal variation of the restriction policies to identify their effect. Mobility restrictions significantly reduced employment, accounting for approximately a quarter of the total job loss between February and April of 2020. The remaining three quarters of the job losses could be attributed to the disease's regional patterns and other epidemiological and economic factors affecting the whole country. Therefore, we should expect important employment losses even in the absence of such restrictions. We also assess the effect of restrictions on the intensive margin, finding negative, although smaller effects on the number of hours worked and wages. Most of the employment effect is driven by salaried workers, while self-employment was more responsive to the disease spread. Finally, we find that women are disproportionally affected: mobility restrictions account for a third of the recent increase of the gender gap in salaried employment.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".