One step forward, two steps back? The fading contours of (in)justice in competing discourses on climate migration
Bibliographic record
Abstract
In recent debates on climate change and migration, the focus on the figure of ‘climate refugees’ (tainted by environmental determinism and a crude understanding of human mobility) has given ground to a broader conception of the climate–migration nexus. In particular, the idea that migration can represent a legitimate adaptation strategy has emerged strongly. This appears to be a positive development, marked by softer tones that de‐securitise climate migration. However, political and normative implications of this evolution are still understudied. This article contributes to filling the gap by turning to both the ‘climate refugees’ and ‘migration as adaptation’ narratives, interrogating how and whether those competing narratives pose the question of (in)justice. Our analysis shows that the highly problematic ‘climate refugees’ narrative did (at least) channel justice claims and yielded the (illusory) possibility of identifying concrete rights claims and responsibilities. Read in relation to the growing mantra of resilience in climate policy and politics, the more recent narrative on ‘migration as adaptation’ appears to displace justice claims and inherent rights in favour of a depoliticised idea of adaptation that relies on the individual migrant's ability to compete in and benefit from labour markets. We warn that the removal of structural inequalities from the way in which the climate–migration nexus is understood can be seen as symptomatic of a shrinking of the conditions to posing the question of climate justice.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.052 |
| Scholarly communication | 0.015 | 0.022 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.010 |
| 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".