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Record W7013031593

Intimate Labors

2008· article· en· W7013031593 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsnot available
FundersUniversity of California, DavisUniversity of California, Santa BarbaraUniversity of ConnecticutLondon Metropolitan UniversityUniversity of Wisconsin-MadisonYale University
KeywordsThursdayAttendanceLeagueEveningGraduate studentsMorning
DOInot available

Abstract

fetched live from OpenAlex

Over fifty scholars—researchers from all the UC campuses with Women’s Studies programs, professors from major Ivy League and state universities, and participants from Canada, Britain, Korea, and South Africa—came to UCSB for a three day conference on “Intimate Labor” the first weekend of October. In conjunction with the conference, Eileen Boris, the co-organizer, held a first-year seminar; the fifteen students from the seminar attended the sessions; so did graduate students and faculty from UCSB and other campuses (particularly UCLA and UCB) who were not on the program, as well as the general public for the opening keynote on Thursday evening and some plenary sessions. Overall attendance averaged 80 per plenary and keynote session, with the first two sessions—Thursday open keynote to the public hitting around a hundred persons and Friday morning keynote/first panel, over hundred to overflow into the corridors the McCune Conference room at the Interdisciplinary Humanities Center, where most of the conference took place.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.010
Scholarly communication0.0050.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0430.005

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 head0.029
GPT teacher head0.250
Teacher spread0.221 · 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
GenreEmpirical

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
Published2008
Admission routes1
Has abstractyes

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