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Record W4415273313 · doi:10.28968/cftt.v11i2.45635

Introduction to the Tenth Anniversary section of Catalyst

2025· article· W4415273313 on OpenAlexaff
Catalyst editorial collective, Kiran Pienaar, Irina Aristarkhova, Robyn Lee, Thao Phan, Xan Chacko, Carina Truyts, Marika Cifor

Bibliographic record

VenueCatalyst Feminism Theory Technoscience · 2025
Typearticle
Language
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTechnoscienceScholarshipAlterityMetaphorConversationSection (typography)Field (mathematics)Assemblage (archaeology)Negotiation

Abstract

fetched live from OpenAlex

In preparing the tenth anniversary section of Catalyst, the current editorial team met to reflect on the legacy, politico-ethical vision and future of the journal. Using the introduction to the inaugural issue as a prompt for our reflections, we discussed what makes the journal distinctive, how it has contributed to the field of technoscience, the intellectual inheritance of feminist scholarship on which our work builds and the generative associations materialised through the metaphor of a catalyst. Our discussion was also guided by the following questions: What kind of topics do you observe are the most current within the field of feminist technosciences? Since you started working at Catalyst, has your perception of feminist technoscience as a field changed? If so, how? How does the current geo-political climate affect your thoughts on feminist technoscience and vice versa? As wide-ranging and capacious as feminist technoscience, the discussion also included lively reflections on the catalytic qualities of bacteria and the ways in which they participate in life-giving processes of kin-making. In the spirit of capturing both the unique voices of the editorial team and the relational assemblage of the conversation as it unfolded, we present it below in conversation-style format. This opening discussion offers a rich companion piece to the reflections of former editorial teams presented in the anniversary section, surfacing the ways in which Catalyst continues to be a playground for alterity and a safe harbor in this historic moment.

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)0.018
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.052
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0140.004
Open science0.0020.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0520.022

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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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
GenreEditorial

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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