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Record W7051536010

outside the lines

2017· book· en· W7051536010 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2017
Typebook
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionHonourQueerMainstreamHuman sexualityNarrativeFeminismImmigration
DOInot available

Abstract

fetched live from OpenAlex

The exhibition Outside The Lines features 10 artists who represent the beyond and within of lines through their artistic practices. This exhibition brings together diverse ways of working with materials to show qualities of living that sit outside of mainstream perception and narrative. Lines have been drawn to mark difference - to keep difference in line. \n \nThese artists share works that question the lines that have been drawn to mark difference – to keep difference in line. They collaborate with autistic experience to challenge notions of independence and care narratives; explore the daily experiences of living with disability that are uniquely humourous, difficult, or lovely; draw queer sexuality and gender through memory fragments; investigate the lived experience of existence with queer and immigrant identity; question the fragmentation of gender, feminism and the body; and challenge the dominant medical and pharmaceutical narratives of experience with cancer. \n \nThis exhibition is held in conjunction with the international conference “Lives Outside the Lines: Gender and Genre in the Americas, A Symposium in Honour of Marlene Kadar.” Kadar is a noted Canadian feminist studies and life writing scholar whose research interests clustered around issues of gender and genre with special attention given to trauma and illness studies, archival methodologies, and transnational themes in the Americas.

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.113
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1130.018

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 head0.013
GPT teacher head0.178
Teacher spread0.164 · 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
Published2017
Admission routes1
Has abstractyes

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