MétaCan
Menu
Back to cohort
Record W3139493728 · doi:10.3167/sa.2020.640407

No One Can Hold It Back

2020· article· en· W3139493728 on OpenAlexafffund
Carlota McAllister

Bibliographic record

VenueSocial Analysis · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaYork UniversityUniversity of Pennsylvania
KeywordsSloganPoliticsVictoryAgency (philosophy)SovereigntyPhenomenonEnvironmental ethicsAction (physics)TranquillitySociologyUnitary stateFlooding (psychology)AestheticsEpistemologyHistoryLawPolitical sciencePhilosophyPsychology

Abstract

fetched live from OpenAlex

The slogan “Water is Life” rallies anti-extractive movements across the Americas. Critical theorists, however, decry the circumscription of environmental politics by the vitalist attribution of political agency to liveliness. This article tempers that critique by juxtaposing it to the Catholic Church’s claims to sovereignty over life, deploying the resulting slippages between water and life to explore the theopolitical potencies that emerge in water’s oscillations between non-life and the divine. Exploring these oscillations in a dam conflict in Chilean Patagonia, I argue that they allowed a flooding phenomenon on a river threatened with damming to be heard as a prophetic call to action. The uprising that followed produced a rare victory for dam opponents, suggesting that a theopolitics of life has powers that exceed vitalism.

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)0.005
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.017
Scholarly communication0.0130.021
Open science0.0020.008
Research integrity0.0070.018
Insufficient payload (model declined to judge)0.0690.039

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 head0.063
GPT teacher head0.335
Teacher spread0.272 · 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 designNot applicable
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

Citations9
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueSocial AnalysisSame topicGeographies of human-animal interactionsFrench-language works237,207