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Record W3093162091 · doi:10.1177/0306312720966649

The financial market of ideas: A theory of academic social media

2020· article· en· W3093162091 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.

Bibliographic record

VenueSocial Studies of Science · 2020
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScholarshipConstruct (python library)Social mediaSociologyScholarly communicationPublic relationsValue (mathematics)Social media analyticsSocial sciencePolitical sciencePublishingComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Millions of scholars use academic social media to share their work and construct themselves as legitimate and productive workers. An analysis of Academia.edu updates ideas about science as a 'marketplace of ideas'. Scholarly communication via social media is best conceptualized as a 'financial market of ideas' through which academic value is assigned to publications and researchers. Academic social media allow for the inclusion of scholarly objects such as preprint articles, which exceed traditional accounting systems in scholarly communication. Their functioning is based on a valorization of derived qualities, as their algorithms analyze social interactions on the platform rather than the content of scholarship. They are also oriented toward the future in their use of data analytics to predict research outcomes.

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)0.040
metaresearch head score (Gemma)0.260
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.260
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.117
Science and technology studies0.0010.016
Scholarly communication0.0000.000
Open science0.0040.002
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 head0.630
GPT teacher head0.586
Teacher spread0.044 · 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