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Record W4297998264 · doi:10.32920/ryerson.14647092.v2

Terms of restriction

2022· preprint· en· W4297998264 on OpenAlexaboutno aff
Benjamin M. Lewis

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetSurpriseCommissionPoliticsBusinessPublic relationsLegislationPolitical scienceAdvertisingInternet privacySociologyLawWorld Wide Web

Abstract

fetched live from OpenAlex

"Initially developed by universities and the military, the speed at which the Internet was embraced by the general public during the mid-nineteen-nineties took governments and commercial interests by surprise. It allowed for a new form of discourse, where anyone could log-on and, at no additional cost, enter into conversations and debates with millions of other Internet users. This new medium for communicating information allowed individuals to overcome existing financial and spatial barriers and thereby engage in new forms of critical political dialogue. Internet communities have flourished and existing corporate media companies, experienced at producing and distributing content to audiences of consumers, have had to adapt to audiences that increasingly demand the right to create and distribute content themselves. Many governments, Canada included, have chosen to leave the Internet and its infrastructure largely unregulated, believing that existing legislation would suffice (Canadian Radio Television and Telecommunications Commission. CRTC Won't Regulate the Internet). In contrast to traditional media enterprises already dominated by commercial interests, the Internet seemed to be a medium where commercial and public interests could successfully coexist, and where individuals could engage in critical dialogue, share ideas, and shape discourse and opinions offline as well as online."--Introduction.

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)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.148
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0060.007
Scholarly communication0.0130.012
Open science0.0030.009
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.1480.116

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 head0.073
GPT teacher head0.373
Teacher spread0.300 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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