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Record W4235166488 · doi:10.32920/ryerson.14657505

Racism, the environment, and persecution : environmental refugees in Tuvalu

2021· preprint· en· W4235166488 on OpenAlexaffabout
Natasha Mann

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRefugeeEnvironmentalismNewspaperPersecutionRacismGovernment (linguistics)PoliticsPolitical scienceDevelopment economicsPolitical economySociologyLawEconomics

Abstract

fetched live from OpenAlex

This paper explores the concept of environmental refugees through a literature review and discourse analysis of media coverage on Tuvalu. Tuvalu is predicted to be the first nation lost to sea level rise and its government has been active in attempting to secure a place of asylum for its citizens. Although the term 'environmental refugee' is not an official one, it is widely used. Therefore, a case study is used to illustrate how environmental refugees are constructed in the public eye. Using political economy and political ecology approach, the power dynamics that lead to disproportionate environmental destruction in poor, racialized areas as well as unequal access to migration are questioned. Looking at two major newspapers each from Canada, the US, Australia, and New Zealand, and one from Tuvalu, the discourse surrounding environmental refugees reveals how the term is constructed and used for varying agendas, from environmentalism to racial 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.067
GPT teacher head0.304
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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