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Record W4306253448 · doi:10.1002/pra2.641

Investigating Open Access Publishing Practices of Early and <scp>Mid‐Career</scp> Researchers in Humanities and Social Sciences Disciplines

2022· article· en· W4306253448 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Association for Information Science and Technology · 2022
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPublishingAudience measurementDescriptive statisticsLibrary scienceScholarly communicationOpen peer reviewCitationPsychologyPolitical scienceAdvertisingComputer sciencePlant biologyBusiness

Abstract

fetched live from OpenAlex

Abstract Although open access (OA) to research outputs has been proven to improve research readership, citation, and impact, the uptake of OA in some disciplines has remained low. In this paper, we investigated and compared OA publishing practices of early career and mid‐career researchers in the Humanities, Arts, and Social Sciences (HASS) disciplines in Canada. The descriptive survey design with the use of online questionnaire was employed. Participants were drawn from a group of 15 public research universities via their openly available emails on university websites. Survey data was analyzed with descriptive and inferential statistics. Findings show that in the last three years, 74.1% of mid‐career researchers have published in OA journals, compared to 63.1% of early career researchers. However, OA publishing of monographs (21.3%) and conference proceedings (29.9%), as well as the frequency and extent OA publishing remains low among all participants. ANOVA results (F [2, 218] = 3.683, p = .027, 𝜂 2 = .033) showed that 3.3% of the variance in researchers' OA publishing frequency can be attributed to their disciplines. Overall, OA publishing among researchers in the HASS disciplines is still low. Hence, there is a need to identify factors that facilitate or hinder HASS researchers' OA publishing.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchBibliometricsOpen science
Domain: Reporting · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptScholarly communicationOpen science
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.055
metaresearch head score (Gemma)0.208
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication, Open science
Consensus categoriesMetaresearch, Bibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0550.208
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0200.079
Science and technology studies0.0020.002
Scholarly communication0.0120.026
Open science0.0050.009
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 head0.674
GPT teacher head0.562
Teacher spread0.111 · 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