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Record W2255587629 · doi:10.17705/1jais.00419

Ideational Influence, Connectedness, and Venue Representation: Making an Assessment of Scholarly Capital

2016· article· en· W2255587629 on OpenAlexaff
Michael J. Cuellar, Hirotoshi Takeda, Richard Vidgen, Duane Truex

Bibliographic record

VenueJournal of the Association for Information Systems · 2016
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSocial connectednessPublicationPromotion (chess)Representation (politics)Work (physics)Capital (architecture)SociologyTest (biology)Public relationsQuality (philosophy)Political sciencePsychologySocial psychologyEpistemologyLawHistoryEngineering

Abstract

fetched live from OpenAlex

Assessing the research capital that a scholar has accrued is an essential task for academic administrators, funding agencies, and promotion and tenure committees worldwide. Scholars have criticized the existing methodology of counting papers in ranked journals and made calls to replace it (Adler & Harzing, 2009; Singh, Haddad, & Chow, 2007). In its place, some have made calls to assess the uptake of a scholar’s work instead of assessing “quality” (Truex, Cuellar, Takeda, & Vidgen, 2011a). We identify three dimensions of scholarly capital (ideational influence (who uses one’s work?), connectedness (with whom does one work?) and venue representation (where does one publish their work?)) in this paper as part of a scholarly capital model (SCM). We develop measurement models for the three dimensions of scholarly capital and test the relationships in a path model. We show how one might use the measures to evaluate scholarly research activity.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.008
Science and technology studies0.0010.003
Scholarly communication0.0050.008
Open science0.0010.005
Research integrity0.0010.001
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 head0.271
GPT teacher head0.543
Teacher spread0.272 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
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

Citations28
Published2016
Admission routes1
Has abstractyes

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