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Record W4415273455 · doi:10.28968/cftt.v11i2.45590

Reflections on Catalyst’s legacy and future

2025· article· W4415273455 on OpenAlexaff
Patrick Keilty, Michael Murphy, Banu Subramaniam, Irina Aristarkhova, Kiran Pienaar

Bibliographic record

VenueCatalyst Feminism Theory Technoscience · 2025
Typearticle
Language
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEthosScholarshipConversationFeminismConversation analysis

Abstract

fetched live from OpenAlex

To mark the ten-year anniversary of Catalyst: Feminism, Theory, Technoscience, former and current editors reflect on the journal's origins, its contributions to feminist technoscience, and their aspirations for Catalyst in the next ten years and beyond. The discussion was recorded on Zoom, transcribed verbatim and edited for clarity. Presented in the original conversation format, the piece offers insights into the rich histories and intellectual legacies that have shaped Catalyst, and the feminist ethos that underpins the journal's scholarship and editorial practices.

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)0.024
metaresearch head score (Gemma)0.039
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.024
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0070.010
Scholarly communication0.0220.015
Open science0.0020.006
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0090.003

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 head0.298
Teacher spread0.285 · 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
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

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