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Record W2601298734 · doi:10.6017/ital.v36i1.9598

Reference Rot in the Repository: A Case Study of Electronic Theses and Dissertations (ETDs) in an Academic Library

2017· article· en· W2601298734 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

VenueInformation Technology and Libraries · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsStratified samplingLibrary scienceSample (material)Computer scienceWorld Wide WebPhysicsMathematicsStatisticsThermodynamics

Abstract

fetched live from OpenAlex

This study examines ETDs deposited during the period 2011-2015 in an institutional repository, to determine the degree to which the documents suffer from reference rot, that is, linkrot plus content drift. The authors converted and examined 664 doctoral dissertations in total, extracting 11,437 links, finding overall that 77% of links were active, and 23% exhibited linkrot. A stratified random sample of 49 ETDs was performed which produced 990 active links, which were then checked for content drift based on mementos found in the Wayback Machine. Mementos were found for 77% of links, and approximately half of these, 492 of 990, exhibited content drift. The results serve to emphasize not only the necessity of broader awareness of this problem, but also to stimulate action on the preservation front.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.006
Open science0.0000.000
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 head0.028
GPT teacher head0.240
Teacher spread0.213 · 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