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Record W3081534626 · doi:10.1386/jem_00033_1

#NoGoingBack: Queer leaps at the intersection of protest and COVID-19

2020· article· en· W3081534626 on OpenAlexaff
Jin Haritaworn

Bibliographic record

VenueJournal of Environmental Media · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsYork University
Fundersnot available
KeywordsQueerRacismLEAPSPunkAestheticsSociologyHistoryPolitical scienceMedia studiesGender studiesArtArt history

Abstract

fetched live from OpenAlex

The concurrency of quarantine and protest has highlighted the trappings of a modernist realism whose conservative solutions reveal a paucity of methods and dreams. The wins that the uprisings against anti-Black police violence have put on the horizon, from the dismantling of carceral institutions to the uplifting of alternatives, have been long seeded by social movements that demanded the impossible. This includes ancestors, many of whom Black, queer and abolitionist, who prepared to take fantastic leaps, in the words of the Combahee River Collective. The following meditation holds up this legacy in order to reckon with the racism accompanying this latest crisis, from the Orientalist origin story of the coronavirus to a global quarantine paradigm that is haunted by racial capitalism. At the dystopic crossroad of the pandemic and the uprisings, a multiracial and multi-species spectre of planetary interdependence appears. This is illustrated by a mutual aid movement that uses digital and offline tactics in order to norm beyond the normal. In the place of a state-led surveillance and a single-issue environmentalism that are hostile to those most vulnerable to the virus, an urban environmental justice becomes palpable whose methods are queer.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.011
Scholarly communication0.0110.007
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0430.003

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 head0.042
GPT teacher head0.250
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2020
Admission routes1
Has abstractyes

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