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Record W2289917642

Dear Videogames, Letter Writing and the Dear Ada Project

2014· article· en· W2289917642 on OpenAlexaff
Emily Flynn-Jones

Bibliographic record

VenueLoading... · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicAutobiographical and Biographical Writing
Canadian institutionsYork University
Fundersnot available
KeywordsQueerSubject (documents)SituatedPoliticsGender studiesHistorySociologyComputer scienceLibrary scienceLawPolitical scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Dear Ada is a Feminists in Games supported project which invites members of the videogame community to submit letters on the subject of gender and games. Letter writing as part of a long feminist tradition of life writing is chronicled by Margaretta Jolly in In Love and Struggle, which spans generations of writers including letters between mothers and daughters, queer love letters, political movements and letters after the advent of email. This article reflects on the Dear Ada letters and how the project is situated within a larger feminist epistolary history.

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)0.007
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 score0.018
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.006
Scholarly communication0.0110.004
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0180.005

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 head0.014
GPT teacher head0.202
Teacher spread0.188 · 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
Published2014
Admission routes1
Has abstractyes

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