MétaCan
Menu
Back to cohort
Record W3214611157 · doi:10.1139/facets-2021-0100

Self-promotion and the need to be first in science

2021· article· en· W3214611157 on OpenAlexaffvenue
Douglas W. Morris, Erin MacGillivray, Elyse N. Pither

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsLakehead University
Fundersnot available
KeywordsNoveltyScholarshipHubrisHumilityPromotion (chess)Subject (documents)PerceptionPolitical sciencePsychologyPublic relationsSociologyEngineering ethicsEpistemologySocial psychologyComputer scienceLawHistoryLibrary sciencePhilosophyEngineering

Abstract

fetched live from OpenAlex

Scientists, like all humans, are subject to self-deceptive valuations of their importance and profile. Vainglorious practice is annoying but mostly harmless when restricted to an individual’s perception of self-worth. Language that can be associated with self-promotion and aggrandizement is destructive when incorporated into scientific writing. So too is any practice that oversells the novelty of research or fails to provide sufficient scholarship on the uniqueness of results. We evaluated whether such tendencies have been increasing over time by assessing the frequencies of articles claiming to be “the first”, and those that placed the requirement for scholarship on readers by using phrases such as “to the best of our knowledge”. Our survey of titles and abstracts of 176 journals in ecology and environmental biology revealed that the frequencies of both practices increased linearly over the past half century. We thus warn readers, journal editors, and granting agencies to use caution when assessing the claimed novelty of research contributions. A system-wide reform toward more cooperative science that values humility, and abhors hubris, might help to rectify the problem.

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 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)0.021
metaresearch head score (Gemma)0.038
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0180.213
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0010.001
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 head0.493
GPT teacher head0.543
Teacher spread0.050 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFACETSSame topicscientometrics and bibliometrics researchFrench-language works237,207