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Record W2974700034 · doi:10.18432/ari29504

A Tapestried Review of the Fully-virtual, Non-traditional (Un)conference "MAKING shiFt HAPPEN: Female Academics Creating Personal and Professional Alchemy in the Academy," Co-convened by Alison Black and Rachael Dwyer

2019· review· en· W2974700034 on OpenAlexaffvenue
Melinda M. Lewis, Helen Grimmett, Briony Lipton, Susan Walsh, Barbara Bickel, Sandra Elsom, Marguerite Westacott, Claire Green, Amelia Walker

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2019
Typereview
Languageen
FieldSocial Sciences
TopicUniversity Challenges and Reforms
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsAlchemyParadigm shiftSociologyMedia studiesEngineering ethicsEngineeringHistoryArt historyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

These storied and aesthetic offerings are presented as an alchemic tapestry of experiences and responses to the conference MAKING shiFt HAPPEN. This innovative (un)conference was fully virtual, and connected us across disciplines, countries and time zones. In this review we respond to how MAKING shiFt HAPPEN offered flexible, sustainable and inclusive options for us, women in academia, to engage with meaningful ideas and with other women around the world.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.999
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.255
GPT teacher head0.471
Teacher spread0.217 · 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.

Study designQualitative
Domainnot available
GenreReview

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

Citations2
Published2019
Admission routes2
Has abstractyes

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