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Record W4244881406 · doi:10.1002/asi.20744

Long‐term variations in the aging of scientific literature: From exponential growth to steady‐state science (1900–2004)

2007· article· en· W4244881406 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

VenueJournal of the American Society for Information Science and Technology · 2007
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsObsolescencePhenomenonPeriod (music)Term (time)Scientific literatureHistoryDemographySociologyEpistemologyAestheticsPhilosophyBiologyPhysics

Abstract

fetched live from OpenAlex

Abstract Despite a very large number of studies on the aging and obsolescence of scientific literature, no study has yet measured, over a very long time period, the changes in the rates at which scientific literature becomes obsolete. This article studies the evolution of the aging phenomenon and, in particular, how the age of cited literature has changed over more than 100 years of scientific activity. It shows that the average and median ages of cited literature have undergone several changes over the period. Specifically, both World War I and World War II had the effect of significantly increasing the age of the cited literature. The major finding of this article is that contrary to a widely held belief, the age of cited material has risen continuously since the mid‐1960s. In other words, during that period, researchers were relying on an increasingly old body of literature. Our data suggest that this phenomenon is a direct response to the steady‐state dynamics of modern science that followed its exponential growth; however, we also have observed that online preprint archives such as arXiv have had the opposite effect in some subfields.

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)0.057
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0570.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0270.266
Science and technology studies0.0010.005
Scholarly communication0.0030.004
Open science0.0050.001
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 head0.119
GPT teacher head0.464
Teacher spread0.345 · 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