Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We analyze the impact on crime of millions of refugees who entered and stayed in Turkey as a result of the civil war in Syria. Using a novel administrative data source on the flow of offense records to prosecutors’ offices in 81 provinces of the country each year, and utilizing the staggered movement of refugees across provinces over time, we estimate instrumental variables models that address potential endogeneity of the number of refugees and their location and find that an increase in the number of refugees leads to more crime. We estimate that the influx of refugees between 2012 and 2016 generated additional 75,000 to 150,000 crimes per year, although it is not possible to identify the distribution of these crimes between refugees and natives. Additional analyses reveal that a low‐educated native population has a separate, but smaller, effect on crime. Our results underline the need to quickly strengthen the social safety systems, to take actions to dampen the impact on the labor market, and to provide support to the criminal justice system for mitigating the repercussions of massive influx of individuals into a country, and to counter the social and political backlash that typically emerges in the wake of such large‐scale population movements.
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.
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it