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Record W4393002543 · doi:10.5509/2024972-art2

Hidden Flows: Hydropower and the Rhythms of Development on the Mekong

2024· article· en· W4393002543 on OpenAlexvenueno aff
Andrew Alan Johnson

Bibliographic record

VenuePacific Affairs · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHydropowerHydroelectricityGeographyMidstreamThreatened speciesChinaEcologyArchaeology

Abstract

fetched live from OpenAlex

The Xayaburi Hydroelectric Power Project entered operation in October 2019. After this the Mekong started to behave strangely—the water ran blue and clear instead of red and silty, and the great backflow of the river into Cambodia's Tonle Sap Lake arrived off schedule or, at times, threatened to not arrive at all. Villagers who had remained ambivalent or apathetic about hydropower issues suddenly found themselves facing a radically altered world, where a seemingly distant power was able to dramatically alter the nature of their every day. These shifts introduced an arrhythmia into the hydroscape: ecological, fishing, and religious cycles adapted to a seasonal river were off sync with power demands. The radical alteration that dams make to the landscape, in the promise of irrigation, electrification, and the sheer feat of changing a river, are a tangible symbol of the state's power over its land. But with a deep look into hydropower projects—in this case, the dams across the midstream of the Mekong in Laos and China—the story grows more convoluted. Here are conflicting narratives of power: state-focused, international, and royalist; as well as religious, ecological, and hydrosocial. Here, too, as I found in my eight years of fieldwork in Lao-speaking Thailand, is an alteration in time, where the rhythms of the river change the rhythms of life, and where the cyclical riparian clock clashes with a future-oriented developmentalist notion of time.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.017
GPT teacher head0.268
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 teacher head, 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

Citations0
Published2024
Admission routes1
Has abstractyes

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