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Record W6992435737

Liquid Laws: Extractivism and Unstable Authority

2020· other· en· W6992435737 on OpenAlexafffund

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typeother
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsYork University
FundersYork University
KeywordsColonialismContext (archaeology)State (computer science)NarrativeWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis concerns the co-constitution of extractivism and claims to authority, particularly in contexts where the legal narrative hides the ways that extractivism is facilitated. I examine how law implicitly structures extractivism, as well as how states use extractivism to generate authority. I look at this relationship in the context of international legal debates over the Antarctic Treaty, and a history of extractive interventions by the settler colonial state towards the Murray-Darling River Basin in south-eastern Australia. The way I read claims to authority engages both the violence and instability of these claims. The specific ways in which the relationship between extractivism and authority is enacted in these contexts depends in part on the spatial construction of water and ice. The co-constitution of extractivism and authority in these examples is also revealed both through imperial imaginaries that have material effects, and material practices that build a colonial legal imaginary.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.070
Scholarly communication0.0110.012
Open science0.0010.009
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.013
GPT teacher head0.186
Teacher spread0.174 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes2
Has abstractyes

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