Immigration, Intended Settlement Patterns, and their Dynamics in the United States, 1980-1990
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
The intended destination pattern of immigrant settlement is a potentially dynamic choice, with fiscal and adjustment implications for both immigrants and the receiving area. Using yearly data from the Immigration and Naturalization Service, the intended immigrant settlement pattern is examined within a pooled cross-section time-series framework, focusing on the twenty-five largest U.S. metropolitan areas between 1980 and 1990. Trends in settlement patterns differentiate between the immigration streams from various sources and immigrant classes. Although no systematic differences were found across national origin groups, the results show that the choice of the intended destination is a dynamic process. Characteristics and determinants of settlement choice, particularly with respect to family and friends effects (as opposed to economic effects), change over time.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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