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Record W4380680033 · doi:10.32920/23503674.v1

Trouble In Paradise: Improving The Discoverability Of Circum-Caribbean Materials Through Enhanced Cataloguing Practices

2023· preprint· en· W4380680033 on OpenAlexaff
Alexandra Gooding

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsToronto Metropolitan University
FundersUniversity of Cambridge
KeywordsDiscoverabilityAuthority controlCommonwealthMainstreamBespokeParadiseUsabilityIndex (typography)Library scienceHistoryWorld Wide WebPolitical scienceControl (management)Computer scienceArt historyArchaeologyLaw

Abstract

fetched live from OpenAlex

This thesis examines how the Circum-Caribbean region’s cultural and geographic complexity make it difficult to describe or index materials relevant to this region using mainstream authority controls available in galleries, libraries, archives, and museums (GLAMs). The majority of widely used controls in GLAMs have Western-centralised worldviews and are rigid in nature, thereby incapable of accommodating the fluidity necessary to accurately denote the complex Circum-Caribbean. This paper applies methodologies to the Getty Thesaurus of Geographic Names and the West Indian Postcard Collection at the Cambridge University Library’s Royal Commonwealth Society department to argue that expanding the vocabulary and applications of an authority control can improve the discoverability of collection materials pertinent to the Circum-Caribbean. My results and observations coupled with brief reviews of two bespoke authority controls lead to recommendations on how to improve authority controls, particularly how to decolonise them and improve their usability for non-Western places and cultures.

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)0.008
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0030.003
Scholarly communication0.0120.020
Open science0.0020.007
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.003

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 head0.104
GPT teacher head0.366
Teacher spread0.263 · 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 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
Published2023
Admission routes1
Has abstractyes

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Same topicPhilippine History and CultureFrench-language works237,207