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Record W4307720464 · doi:10.1080/00076791.2022.2123470

Take nothing for granted: Expanding the conversation about business, gender, and feminism

2022· article· en· W4307720464 on OpenAlex
Jennifer Aston, Hannah Barker, Gabrielle Durepos, Shenette Garrett-Scott, Peter James Hudson, Angel Kwolek-Folland, Hannah Dean, Linda Perriton, Scott Taylor, Mary Yeager

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBusiness History · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsConversationFeminismNothingSociologyPolitical scienceGender studiesPublic relationsEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Special Issues can surprise and frustrate in equal measure. Editorial expectations are often upended. The submissions imagined are not always those received or in the numbers anticipated. The questions that frame the call for papers seldom carry the same weight at the beginning and end of the editorial process. Yet somehow the academic publishing industry survives and thrives, commodifying scholarly inquiry based on virtually free labour inputs. The best readers should take nothing for granted, including editorial and publishing processes and 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.206
Teacher spread0.172 · 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