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Record W1510487290 · doi:10.5281/zenodo.10031937

Long-Term Patterns in the Aging of the Scientific Literature, 1900–2004

2007· article· en· W1510487290 on OpenAlexaff
Vincent Larivière

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsObsolescencePhenomenonScientific literatureTerm (time)Period (music)DemographyHistoryPositive economicsSociologyEpistemologyEconomicsPhilosophyBiologyAesthetics

Abstract

fetched live from OpenAlex

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 paper aims at studying the evolution of the aging phenomenon and, in particular, how citation half-lives are changing over more than 100 years of scientific activity. It shows that the average and median age of cited literature has undergone several changes over the period. Specifically, the two World Wars had the effect of raising the average and median age of the cited literature significantly. Moreover, and contrary to a widely-held belief, the age of cited material has risen continuously since the mid-60s. Among the possible explanations for this counter-intuitive phenomenon, the most probable is the levelling off of the growth of scientific literature related to the steady-state dynamics of modern science that follows its exponential growth.

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)0.003
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.012
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.433
GPT teacher head0.557
Teacher spread0.124 · 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 designObservational
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

Citations7
Published2007
Admission routes1
Has abstractyes

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