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River Energies

2025· article· en· W4417451315 on OpenAlexaffvenueabout
David Jaclin, Nicolas Cadieux, Marie Lecuyer

Bibliographic record

VenueAnthropologica · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsIndigenousHydropowerHydroelectricityBlackwaterWater scarcityState (computer science)Hydrology (agriculture)WitnessToilet

Abstract

fetched live from OpenAlex

From 2024 and its spring débâcle to 2025’s first fall snow, an ethnographical collective of researchers from the University of Ottawa took off from campus for two ‘‘river semesters.’’ Following a speculative drop of water taken from the Kichissippi River (the Ottawa River in English or rivière des Outaouais in French), we fieldworked in, on and around water for an experience in elemental anthropology. We engaged with the various circulations sustained by the river flow, at times geo-chemical, at times eco-cosmological, always anthropogenic. From the sacred Anishinaabe island of Asinabka, to the adjacent massive dam of Chaudière Falls, through the headquarters of Brookfield Energy (a major hydroelectricity trading firm), to the multimillion-dollar riverfront development called Zibi—with its net zero dream of community living and neighbouring toilet paper factory that heats buildings in the winter—we regarded this sensitive anthropological confluence as a saturated flow (following Ruiz and Jue (2022)). A flow where water is, disparately and at times concomitantly, looked upon as a natural resource, a valuable landscape, a precious witness of perilous climate events to come, an alluring promise, a discomforting oracle or a forthcoming expansion of capital. Along the flooded banks of this continuously changing watercourse, which once was a highway for Indigenous peoples to travel, trade, and strive, and where the parliament of a rather young state now sits, we investigate the pulsating milieu where everything that is to come seems to run from.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.341
Teacher spread0.331 · 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.

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

Citations1
Published2025
Admission routes3
Has abstractyes

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