MétaCan
Menu
Back to cohort
Record W2605178705 · doi:10.1080/14680777.2017.1308410

Tedious: feminized labor in machine-readable cataloging

2017· article· en· W2605178705 on OpenAlex

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

VenueFeminist Media Studies · 2017
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCatalogingProductivityIndustrialisationIBMProcess (computing)Labor relationsSociologyPolitical scienceLabour economicsComputer scienceEconomicsWorld Wide WebLawEconomic growth

Abstract

fetched live from OpenAlex

This essay examines previously unexplored IBM reports and manuals that document the development of Machine-Readable Cataloging (MARC) in the 1960s to understand gendered assumptions manufacturers made about the labor of information retrieval and to ultimately discuss the ways in which MARC transformed the feminized labor of information, making it more diffuse and shifting expectations about productivity. In the process, this essay will show that cataloging, like other forms of women’s labor transformed by technology in the latter part of the twentieth century, has a complicated relationship to the market labor and industrialization. Finally, this essay ends by connecting MARC and feminized labor to the contemporary discussion of BIBFRAME.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.316
Teacher spread0.267 · 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