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Record W4311720770 · doi:10.1177/14744740221142881

Restoring the river, restoring relations: on Anishinaabe artist Michael Belmore’s stone series, <i>Replenishment</i>

2022· article· en· W4311720770 on OpenAlexaff
Nicole Latulippe

Bibliographic record

VenueCultural Geographies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsIndigenousColonialismNarrativeAgency (philosophy)HistoryReciprocity (cultural anthropology)SociologyAnthropologyArchaeologyArtLiteratureEcologySocial science

Abstract

fetched live from OpenAlex

In his work and creative practice, Anishinaabe artist Michael Belmore shows that materials have language and rock tells a story. Belmore’s land-based installation on Manitoulin Island, a three-part granite series titled, Replenishment, tells a story about place that is activated by relationship and reciprocity between people and with the Earth. It reinscribes Indigenous presence on the land, rewrites settler-colonial narratives about place, and broadens the scope and intent of ecological restoration. Drawing on my interactions with the artist and his work during the 2017 Manitoulin Island Summer Historical Institute, a field school on Anishinaabe history, I explore the circulation of knowledge and agency in an Anishinaabe world and consider relationship as essential to decolonizing geography’s engagement with Indigenous peoples and territories. Through rock as mnemonic device, Belmore demonstrates the restorative power of subtle and not so subtle acts of interconnection and relationship.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0240.015
Scholarly communication0.0070.004
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.034
GPT teacher head0.303
Teacher spread0.270 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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