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Record W4324374795 · doi:10.1111/anti.12939

Dams, Diversions, and Development: Slow Resistance and Authoritarian Rule in the Salween River Basin

2023· article· en· W4324374795 on OpenAlexaff
Zali Fung, Vanessa Lamb

Bibliographic record

VenueAntipode · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsYork University
FundersUniversity of MelbourneAustralian Government
KeywordsForegroundingResistance (ecology)AuthoritarianismCONTESTTemporalityPoliticsPolitical sciencePolitical economySociologyLawDemocracyEcology

Abstract

fetched live from OpenAlex

Abstract We engage geography's longstanding debate on what “counts” as resistance by introducing slow resistance to account for temporal‐political strategies against unjust developments, particularly under authoritarian conditions. We draw on over a decade of fieldwork in the Salween River Basin where dams and diversions have been proposed since 1979, including the most recent iteration, the Yuam River water diversion project in Northwest Thailand. We find that resistance by impacted communities and civil society encompasses slow, strategic, and considered actions over time and generations. Such resistance is necessarily protracted to contest developments (re)proposed over decades. By foregrounding the strategic use of time and temporality, we highlight often overlooked actions and strategies of resistance by a diverse range of actors, showing how resistance movements are incremental and interconnected over time, even when “under the radar”. These strategies are key to contesting and (re)shaping the conditions of development in the Basin.

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)0.004
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.015
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.270
Teacher spread0.251 · 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

Citations47
Published2023
Admission routes1
Has abstractyes

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