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Record W2760878772 · doi:10.1080/08109028.2017.1408289

Managing the transition to open access publishing: a psychological perspective

2017· article· en· W2760878772 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

VenuePrometheus · 2017
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of Victoria
FundersEconomic and Social Research CouncilUniversity of ExeterResearch Councils UK
KeywordsPublishingPerspective (graphical)Open access publishingFace (sociological concept)Transition (genetics)Peer pressurePsychologyPublic relationsSocial psychologySociologyPolitical scienceSocial scienceWorld Wide WebComputer scienceLaw

Abstract

fetched live from OpenAlex

Abstract To manage the transition to the open access (OA) model of scholarly publishing, we need to understand better what enables, encourages and inhibits the adoption of OA publishing among scientists, and to appreciate individual differences within disciplines. The study adopts a psychological perspective to elucidate motivations, capabilities and opportunities for OA publishing among bioscientists in the UK. To identify differences within the discipline, bioscientists with starkly different past practices for disclosing research data and technologies were interviewed. The sampled bioscientists face similar obstacles and enablers in their physical environment, but that their motivations and experience of their social environments differ. One group is strongly motivated by their moral convictions and beliefs in benefits of OA and feels peer pressure related to OA. The other group expresses fewer pro-OA beliefs, holds beliefs demotivating OA publishing, but feels pressure from research funders to adopt it. The former group makes more frequent use of OA publishing, which suggests that only those with strong motivations will work to overcome the social and physical obstacles. The individual differences within the discipline suggest that bioscientists are unlikely to respond to OA policies in the same way and, thus, the appropriateness of one-size-fits-all OA policies is questioned.

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)0.037
metaresearch head score (Gemma)0.107
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies, Scholarly communication, Open science
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0370.107
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0150.055
Science and technology studies0.0020.000
Scholarly communication0.1500.008
Open science0.0320.007
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.863
GPT teacher head0.713
Teacher spread0.149 · 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