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Record W4399556417 · doi:10.1386/public_00181_1

Introduction: The Witch Institute

2024· article· en· W4399556417 on OpenAlexaff
Tamara de Szegheo Lang, Emily Pelstring, Dan Vena

Bibliographic record

VenuePublic · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsWitchPoliticsSpace (punctuation)SociologyMedia studiesVisual artsArtPolitical scienceLawLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

In August 2021, The Witch Institute came to life as a seven-day virtual symposium to address the figure of the witch in art and media. For its duration, the symposium served as a collaborative meeting space for emerging and established voices, all of whom were responding to increasingly conservative political climates through critical, intersectional, and multi-modal engagements with the figure of the witch. This issue of PUBLIC represents some of these responses. In this introduction, symposium organizers/issue editors, offer some guiding thoughts to the collection and frame the accompanying voices via conversations of artmaking, activism, ritual, and care.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.072
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0720.028

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 head0.031
GPT teacher head0.239
Teacher spread0.208 · 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
Published2024
Admission routes1
Has abstractyes

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