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Record W2567279352 · doi:10.22230/src.2016v7n2/3a259

Research Commons: Site of Innovation, Experimentation, and Collaboration in Academic Libraries

2016· article· en· W2567279352 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueScholarly and Research Communication · 2016
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsScholarshipDigital scholarshipCommonsDigital libraryScholarly communicationDigital humanitiesKnowledge managementPublic relationsSociologyAcademic libraryPolitical scienceLibrary scienceEngineering ethicsComputer scienceEngineeringPublishing

Abstract

fetched live from OpenAlex

Background: This article examines the role the Research Commons plays in supporting digital scholarship in the academic library.Analysis: Relevant literature from library and information science and digital humanities research was reviewed. An environmental scan of select Research Commons and digital scholarship organizations was completed.Conclusion and implications: The Research Commons model encourages interdisciplinary collaboration and takes a holistic approach to providing support services to scholars throughout the research life cycle. The team-based and interdisciplinary nature of digital scholarship production lends itself well to this model. In addition, the training and technology needs associated with digital scholarship align with expertise housed within the library, making the Research Commons a natural point of connection for scholars and librarians engaged in the creation of new modes of scholarly production.

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)0.024
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly 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 score0.573
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0030.072
Open science0.0020.003
Research integrity0.0000.001
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 head0.262
GPT teacher head0.505
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