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Record W7054849218

Art routes: Locating second-generation black Caribbean Canadian women's perspectives

2022· other· en· W7054849218 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsConstruct (python library)Black BritishBlueprintBlack feminismBlack africanContemporary artBlack swan theory
DOInot available

Abstract

fetched live from OpenAlex

Using visual and performance art, music and photography, Art Routes: Locating Second-Generation Black Caribbean Canadian Women’s Perspectives centers a specifically second-generation discourse using the artwork and lived experiences of second-generation Black women artists—Kamilah Apong, Sandra Brewster, Shaunasea Brown, Anique Jordan, Brianna Roye, Camille Turner and Shi Wisdom. By attending to the contours of Black life in the complex geographies of Toronto and beyond, Art Routes acknowledges and articulates how Black women artists provide blueprints for how Black people can create their own kinds of freedom. Through the nuanced position of second-generation be(long)ing, Art Routes captures the struggle of second-generation Black women artists to engage in new forms of world-making that reevaluate ideas about gender, sexuality, and citizenship, posit new radical strategies of care, and re/define how Black people live within and despite contexts of death and dying. With the understanding that the ability to create is a matter of life and death for Black people, Art Routes offers creative ways to think about Black being in Canada while identifying how Black Canadian women artists imagine and construct more inhabitable environments for themselves and their communities.

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)0.002
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: none
Teacher disagreement score0.039
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0350.009
Scholarly communication0.0120.002
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0260.001

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 head0.008
GPT teacher head0.161
Teacher spread0.153 · 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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Same venueYork University Digital Library (York University)→Same topicMagnetic confinement fusion research→French-language works237,207→