Are We in the Same Boat? The Legacy of Historical Emigration on Attitudes Towards Immigration
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 I analyze the effect of historical emigration on current attitudes towards immigrants and migration policies in central and southern Italy. To do so, I collect data on Italian emigrants by the municipality of last residence from the Ellis Island archives in the period 1892–1924. I estimate, then, the causal effect of emigration on a series of outcomes used to measure attitudes towards immigration through an IV strategy, by exploiting exogenous variation in proximity to departure port to the U.S. during the years 1892‐1924. I find that emigration has a negative and significant long‐run effect on attitudes towards immigration. In particular, higher historical emigration reduces the propensity to open refugees reception centers, social expenditure, volunteers in non‐profit organizations and significantly decreases political support for more inclusive parties.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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