"Inevitable, Undesirable and Threatening": Uncovering State Representations of Climate Migrants in Canada and Australia
Bibliographic record
Abstract
The expression “climate migrant” is increasingly used by policy makers, journalists and scholars to discuss the human impacts of climate change – with some authors evoking apocalyptic scenarios of mass displacement. Climate migration is frequently presented as a future or conditional phenomenon that will impact a variety of actors. States are foremost among these actors as they play a decisive role in legitimizing forms of migration. States decide who is permitted to enter and who is excluded from their territories. As both Canada and Australia have been tipped as potential strategic destinations for the resettlement of climate migrants, their respective governments have begun to discuss the political implications of climate migration. The term “climate migrants” is, however, ill-defined and empirically unsubstantiated. Moreover, it has been mobilized to evoke different meanings, often reflecting colonial and neocolonial biases. In other words, the use of the term reflects political undertones. Understanding how countries use the term is significant as it offers insights on these undertones. By engaging in a thick reading of state publications on climate migrants, I find that Canada and Australia represent climate migrants as an inevitable, undesirable and threatening consequence of climate change. Furthermore, I situate this representation within a broader hegemonic discourse on climate migration and human mobilities that views migrants as (racialized) “others” threatening to destabilize the Global North.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.025 | 0.016 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".