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Record W2405542630 · doi:10.1177/1478210315579983

Open science strategies in research policies: A comparative exploration of Canada, the US and the UK

2015· article· en· W2405542630 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

VenuePolicy Futures in Education · 2015
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOpen scienceOpenness to experienceOpen governmentOpen dataGovernment (linguistics)Political sciencePublic relationsScience policyKey (lock)Public administrationSociologyComputer sciencePsychology

Abstract

fetched live from OpenAlex

Several movements have emerged related to the general idea of promoting ‘openness’ in science. Research councils are key institutions in bringing about changes proposed by these movements, as sponsors and facilitators of research. In this paper we identify the approaches used in Canada, the US and the UK to advance open science, as a step towards understanding how policy in this area is evolving. The findings highlight three broad patterns across the countries, showing that open science is supported not only be the activities of individual research councils, but also through government mandates and inter-council cooperation. These patterns involve efforts to create a digital infrastructure for open science, to foster open access, and to support open data initiatives.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0030.015
Open science0.0050.002
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 head0.414
GPT teacher head0.553
Teacher spread0.139 · 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