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Record W1903266278 · doi:10.29379/jedem.v3i1.54

Open Access to Research. Changing Researcher Behavior Through University and Funder Mandates.

2011· article· en· W1903266278 on OpenAlexafffund
Stevan Harnad

Bibliographic record

VenueJeDEM - eJournal of eDemocracy and Open Government · 2011
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPublicationPublish or perishOrder (exchange)Computer sciencePolitical sciencePublic relationsInternet privacyOpen scienceBusinessWorld Wide WebPublishingLawMathematics

Abstract

fetched live from OpenAlex

The primary target of the worldwide Open Access initiative is the 2.5 million articles published every year in the planet's 25,000 peer-reviewed research journals across all scholarly and scientific fields. Without exception, every one of these articles is an author give-away, written, not for royalty income, but solely to be used, applied and built upon by other researchers. The optimal and inevitable solution for this give-away research is that it should be made freely accessible to all its would-be users online and not only to those whose institutions can afford subscription access to the journal in which it happens to be published. Yet this optimal and inevitable solution, already fully within the reach of the global research community for at least two decades now, has been taking a remarkably long time to be grasped. The problem is not particularly an instance of "eDemocracy" one way or the other; it is an instance of inaction because of widespread misconceptions (reminiscent of Zeno's Paradox). The solution is for the world's research institutions and funders to (1) extend their existing "publish or perish" mandates so as to (2) require their employees and fundees to maximize the usage and impact of the research they are employed and funded to conduct and publish by (3) depositing their final drafts in their Open Access (OA) Institutional Repositories immediately upon acceptance for publication in order to (4) make their findings freely accessible to all their potential users webwide. OA metrics can then be used to measure and reward research progress and impact; and multiple layers of links, tags, commentary and discussion can be built upon and integrated with the primary research.

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)0.035
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.031
Science and technology studies0.0010.000
Scholarly communication0.0080.006
Open science0.0100.033
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.909
GPT teacher head0.664
Teacher spread0.244 · 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

Citations43
Published2011
Admission routes2
Has abstractyes

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