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Record W4377694895 · doi:10.1353/ail.2022.0018

From the Floodland: Countering Extraction, Remembering Relations in Eeyou Istchee

2022· article· en· W4377694895 on OpenAlexaboutno aff
Isabella Huberman

Bibliographic record

VenueStudies in American Indian Literatures · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsSculptureColonialismEvent (particle physics)Reading (process)HistoryMeaning (existential)Art historyArchaeologyArtSociologyLawPhilosophyPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

In this article, I attend to two stories from the floodland of Eeyou Istchee/James Bay, where in the mid-2000s the massive infrastructure of Hydro-Québec’s Eastmain-Rupert project flooded a portion of Eeyouch ancestral lands, submerging Eeyouch grave sites and places of meaning and memory. Reading across literature and public art, and engaging with ghosts and other-than-human presences, I analyse two works rooted in Eeyouch territory and this shared event of colonial resource extraction. The novel Ourse bleue (2007) by Cree-Métis writer Virginia Pésémapéo Bordeleau and the large-scale sculpture Iiyiyiu-Iinuu (2008) by Cree artist Tim Whiskeychan conjure place-based connections to the departed that contend with the recent history of Hydro in Eeyou Istchee. Both pieces model a form of storying in the wake that refuses the smooth passage of Hydro over the dead and suggests that these are relationships to nourish in the present.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.855
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0290.028
Scholarly communication0.0070.007
Open science0.0010.009
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.360
Teacher spread0.340 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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