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Record W2771265035 · doi:10.1111/1365-2664.13040

On the extinction of the single‐authored paper: The causes and consequences of increasingly collaborative applied ecological research

2017· article· en· W2771265035 on OpenAlexaff
Jos Barlow, Philip A. Stephens, Michael Bode, Marc W. Cadotte, Kirsty Lucas, Erika Newton, Martín A. Núñez, Nathalie Pettorelli

Bibliographic record

VenueJournal of Applied Ecology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsEcologyExtinction (optical mineralogy)GeographyEnvironmental resource managementEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

In 1963, Price analysed authorship patterns in chemical science and identified that “…the proportion of multi‐author papers has accelerated steadily and powerfully, and it is now so large that if it continues at the present rate, by 1980 the single‐author paper will be extinct” (Price, 1963). An analysis of all research papers published in Journal of Applied Ecology since 1966 shows that the trends identified by Price also apply to our field: an exponential increase in the mean number of authors per published article has been mirrored by a sharp decline in the proportion of single‐authored papers (Figure 1). From over 60% of all publications in the 1960s, single‐author papers now make up less than 4% (averaged over the past 10 years). Although the single‐author paper has hung on well beyond 1980 in Journal of Applied Ecology, their extinction now appears imminent.

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)0.036
metaresearch head score (Gemma)0.124
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.124
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.012
Science and technology studies0.0060.014
Scholarly communication0.0100.016
Open science0.0030.008
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0150.002

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 head0.070
GPT teacher head0.310
Teacher spread0.240 · 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
DomainIncentives
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

Citations76
Published2017
Admission routes1
Has abstractyes

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