Urban sustainability and the subjective well‐being of migrants: The role of risks, place attachment, and aspirations
Bibliographic record
Abstract
Abstract While material conditions of migrant populations on average tend to improve over time as they become established in new destinations, individual trajectories of material and subjective well‐being often diverge. Here, we analyse how social and environmental factors in the urban environment shape the subjective well‐being of migrant populations. We hypothesise these factors to include (a) perceived social and environmental risk, (b) attachment to place, and (c) migrant aspirations. We analyse data from a cross‐sectional survey of 2641 individual migrants in seven cities across Ghana, India, and Bangladesh. The results show that the persistence of inferior material conditions, exposure to environmental hazards, and constrained access to services and employment affect migrants' subjective well‐being. Hence, social and environmental risks constitute urban precarity for migrants whose social vulnerability persist in their destination. Meeting migration‐related aspirations and developing an affinity to urban destinations have the potential to mitigate negative sentiments from perceived risks. These findings have implications for future urban planning and sustainability.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".