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Record W3126591755 · doi:10.54590/pop.2020.011

The Open Scholarship Commons: Advancing Research for the Public Good

2020· article· en· W3126591755 on OpenAlex
Verletta Kern, Madeline Mundt

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePop! Public Open Participatory · 2020
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipCommonsPublic relationsSpace (punctuation)Digital scholarshipInstitutionService (business)Knowledge sharingPolitical scienceValue (mathematics)Public serviceKnowledge managementSociologyBusinessWorld Wide WebComputer scienceSocial scienceMarketing

Abstract

fetched live from OpenAlex

The ground is shifting at our educational institutions. We are asked to demonstrate the value of our research to a wider public, particularly as public funding comes with requirements of openly sharing funded research results. At the same time, we are witnessing an educational shift from students as consumers of knowledge to students as co-creators of new knowledge. How can libraries, the traditional keepers and guardians of knowledge, grow to support this changing world? Our library will offer a new space that brings together partners at our academic institution to support the entire research cycle from the conception of an idea to the creation and dissemination of new knowledge in service of advancing research for the public good. Through this paper, we will share our process for creating this new space and how it will open opportunities for the production and sharing of scholarship beyond the academy.

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)0.018
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0050.000
Scholarly communication0.0210.006
Open science0.0160.008
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.496
GPT teacher head0.486
Teacher spread0.010 · 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