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Record W2003177722 · doi:10.1002/asi.10165

“I spent 1 ½ hours sifting through one large box. …”: Diaries as information behavior of the archives user: Lessons learned

2002· article· en· W2003177722 on OpenAlexaff
Elaine G. Toms, Wendy Duff

Bibliographic record

VenueJournal of the American Society for Information Science and Technology · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicData Analysis and Archiving
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceData collectionInformation behaviorWorld Wide WebPsychologyMultimediaLibrary scienceSociologySocial science

Abstract

fetched live from OpenAlex

Abstract This article describes how diaries were implemented in a study of the use of archives and archival finding aids by history graduate students. The issues concerning diary use as a data collection technique are discussed as well as the different types of diaries.

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)0.018
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0050.008
Open science0.0030.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.337
Teacher spread0.299 · 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
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

Citations72
Published2002
Admission routes1
Has abstractyes

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Same venueJournal of the American Society for Information Science and TechnologySame topicData Analysis and ArchivingFrench-language works237,207