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Record W4415752627 · doi:10.1016/j.polgeo.2025.103439

Just treatment on a damaged planet: Can we crip one health? And should we?

2025· article· en· W4415752627 on OpenAlexafffund
Mollie Holmberg

Bibliographic record

VenuePolitical Geography · 2025
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsBalsillie School of International Affairs
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of British ColumbiaUnited States Agency for International Development
KeywordsConversationHealth carePower (physics)PoliticsCorporate governanceSocial justiceEconomic JusticeEnvironmental justiceCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Disability justice (DJ) and One Health (OH) are two approaches to jointly addressing human, animal, and environmental health that emerged around the same time in overlapping geographies but twenty years later, remain largely separate. Here I first highlight how DJ movements have long operated across human, animal, and environmental health. I then introduce OH as a movement rooted in the organizing of scientists, healthcare practitioners, and policymakers seeking bridge health governance and care across human, animal, and environmental domains. Its tendency to reproduce colonial, anthropocentric, and ableist power structures in the present emerges from its origins in tropical medicine, disease ecology, and veterinary pathology practiced at sites like zoos and colonial/settler colonial research stations. Given this, I then ask: what would it mean to try to ‘crip’ science and health care currently operating within OH towards the political aims of DJ? In conversation with other critical OH interventions, I raise preliminary concerns emerging from the resonances and tensions between questions of what DJ and OH each want. I argue that considering OH and DJ together this way offers important insights for what constitutes just treatment on a damaged planet as well as the possibilities, dangers, and limitations of different approaches to treating injured more-than-human collectives. Throughout, I draw on digitally archived media and primary source materials, expert interviews with OH practitioners, and broader critical scholarship.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.065
GPT teacher head0.359
Teacher spread0.294 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2025
Admission routes2
Has abstractyes

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