Counting Migrants and Migrations: Comparing Lifetime and Fixed‐Interval Return and Onward Migration
Bibliographic record
Abstract
Abstract: Lifetime measures of return and onward migration that use place of birth may be rather arbitrary, as they may not capture the essence of “home” region and therefore may not adequately represent ties to place, including where an individual grew up or went to school. The recent availability of census data that include information on place of residence five years prior to the census, one year prior, and at the time of the census allow an alternative definition of return and onward migration based upon fixed‐interval data. Employing data from the 1996 Canadian census, in this paper I first compare and examine the incidence, composition, and spatial patterns and explanations of return and onward migration through measures of lifetime and fixed‐interval data. I then suggest a typology of return migration. Findings indicate that although both measures result in similar patterns and demographic effects, fixed‐interval measures provide additional detail into the processes at work. Planned returns among younger and older adults that are most likely associated with education or employment and represent 24 percent of returns define two types of return migration. A third type is more consistent with the stereotypical image of a “failed” migration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".