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Record W4391114221 · doi:10.1386/public_00158_1

Thinking Across Worlds: Pluriversal Potentiality

2023· article· en· W4391114221 on OpenAlexaff
Mary Bunch, Dolleen Tisawii’ashii Manning

Bibliographic record

VenuePublic · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork University
Fundersnot available
KeywordsIndigenousOntologySociologyPoliticsAestheticsEpistemologyConsciousnessAnthropologyArtPhilosophyEcologyPolitical scienceLawBiology

Abstract

fetched live from OpenAlex

Reflecting on the epistemological history of the microscope alongside theories of pluriversality and Anishinaabe mnidoo ontology, “Thinking Across Worlds” addresses the microscope as an instrument of decolonial worlding through two artworks created by the authors. We ask, “How can we think across worlds—microscopic and macroscopic, western and Indigenous, scientific and creative—to transform the present and the future, from ecological devastation and colonial violence to sustainability and decolonial justice?” The art works, titled Gathering and Resonance, are experiments in political ontology, through immersion in other worlds, other versions of reality. In these microscopic hydrospheres, Anishinaabe mnidoo reality prevails. Human viewers are dwarfed by the microscopic mnidoo that surround them. The place of humans is revealed to be a mere part within a multiplicity of relations. Our own interests are eclipsed by the dramas that play out among these minute forms of consciousness.

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)0.004
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 score0.012
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0100.058
Scholarly communication0.0120.022
Open science0.0010.013
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.058
GPT teacher head0.367
Teacher spread0.309 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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