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Record W1551076107 · doi:10.18438/b8wp60

Patron Preferences for Folksonomy Tags: Research Findings When Both Hierarchial Subject Headings and Folksonomy Tags Are Used

2009· article· en· W1551076107 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2009
Typearticle
Languageen
FieldComputer Science
TopicMathematics, Computing, and Information Processing
Canadian institutionsnot available
Fundersnot available
KeywordsFolksonomySubject (documents)Computer scienceInformation retrievalPreferenceConstruct (python library)World Wide WebDatabaseMathematics

Abstract

fetched live from OpenAlex

Objective: With the emergence of folksonomy as an option for subject tagging, discussions have ensued about the costs and benefits of continuing to construct and apply traditional subject headings, given that patrons now can generate their own tags. To date, there are very few databases that allow both systems to coexist.
 
 Methods: Within the full text ETD (Electronic Theses and Dissertations) database at Montana State University, both traditional, hierarchical subject headings and patron applied tags are allowed. Patrons are encouraged to tag and the database even features a browse tag capability and a featured ETD. After 24 months of coexistence, data was gathered and analyzed to determine patron use and preferences when given the option of adding their own tags. 
 
 Results: Very few patrons take advantage of adding their own tags. After 2 years, only 2.5 percent of the ETDs have acquired folksonomy tags. A gradual replacement of LCSH headings by patron tags has not occurred. 
 
 Conclusions: The main preference for patron-generated tags can be characterized as very narrow in application and in general would have been disallowed under a traditional library subject heading scheme. Despite the low usage, the folksonomy tags are a positive focal point and have generated collaboration within the database.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.234
Open science0.0010.000
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 head0.045
GPT teacher head0.309
Teacher spread0.264 · 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