Considering Power and Institutional Change in the Study of Migration’s Impact on Non‐Migrants: Commentary on Schut & Crul (2024) and Keskiner et al. (2024)
Bibliographic record
Abstract
Schut and Crul (2024) and Keskiner et al. (2024) bring much‐needed attention to migration’s impact on host societies. They investigate Dutch non‐migrant parents’ responses to migration‐related issues that arise in their children’s schooling, highlighting the diversity of those responses. Future analyses should move beyond individual analyses to understand broader social changes, how group‐level status shapes institutional responses to migration, and the role that systemic racism or Islamophobia may play in shaping individual and institutional responses to migration. This requires empirical analyses that incorporate participant observation in specific institutions (for example, schools), and attention to organizational decision‐making.
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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 | 0.032 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.044 |
| Scholarly communication | 0.009 | 0.021 |
| Open science | 0.011 | 0.008 |
| Research integrity | 0.042 | 0.047 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".