Bibliographic record
Abstract
Abstract I aim to challenge the standard framework in which systematic exclusion is mistakenly characterised as only a frictional phenomenon that fails to be captured in migrants’ labour market matching mechanisms. Societies organise and rank people in a hierarchical way, not only in terms of individual differences and characteristics but with respect to social groups and categories of people. These macro patterns systematically subject some migrant groups to different forms of exclusion. Social stratification, explained in terms of social identity-based institutional structures, organises labour markets into different destinations like clubs with sharply different sets of opportunities. It functions like a trap for migrants: it reinforces itself by reproducing systems of exclusion and creates dilemmas for migrants. Can migrants organise themselves to avoid such traps? I show that exclusion is endogenous to employment as a type of good in the standard goods typology. Treating different types of employment opportunities as being like clubs, I investigate how migrants join or create alternative employment clubs as a response to real or perceived exclusion from native employment clubs. If these alternative clubs are ‘sticky’ and discourage migrants from trying to join natives’ exclusive employment clubs, the trap becomes inescapable. For migrants to escape the stratification trap, employment should be seen not only as an investment but as a collective action problem structurally targeting exclusion.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".