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Record W2101040365 · doi:10.15173/mjc.v10i0.282

Public Spheres in Private Spaces: How Capital Will Stop the Web’s Democratic Potential

2014· article· en· W2101040365 on OpenAlex
Kyle Brown

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

VenueThe McMaster Journal of Communication · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDeliberationThe InternetPoliticsPolitical scienceDemocracyPublic relationsConversationInformation and Communications TechnologyDeliberative democracyAction (physics)Public sphereSociologyInternet privacyMedia studiesWorld Wide WebComputer scienceLawCommunication

Abstract

fetched live from OpenAlex

In the late 1990s and into the early part of the new millennium, the vast, open, seemingly free space of the Internet allowed for many communication and political science scholars to bask in the optimism of a new communication system that would allow for increased debate, deliberation, and flow of information (Kellner, 1998). Notable scholars like Castells (1996) and Benkler (2006) led the charge of conversation in regards to the network society, and the democratizing impacts that such communication technologies could potentially provide. More recently, Internet optimists, like Shirky (2008, 2011), have expressed the role that digital technologies, mostly in terms of the Internet, can have in allowing for widespread democratizing communication, social movements and political action in its ability to organize and mobilize individuals, both in online discussion spaces, and in the “real” world.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.038
GPT teacher head0.280
Teacher spread0.242 · 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