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Record W2399358312 · doi:10.1177/1354856516648084

Technology, fandom and community in the second media age

2016· article· en· W2399358312 on OpenAlexaff
Rhiannon Bury

Bibliographic record

VenueConvergence The International Journal of Research into New Media Technologies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsAthabasca University
Fundersnot available
KeywordsFandomInteractivitySociologyVirtual communityCitizen journalismParticipatory cultureContext (archaeology)The InternetOnline communitySocial mediaMedia studiesSubjectivityInformation AgeAdvertisingWorld Wide WebComputer sciencePolitical scienceHistory

Abstract

fetched live from OpenAlex

The virtual or online community was considered by Mark Poster (1995) to be central to what he called the second media age, marked as distinct from the first media age by new modes interactivity and subjectivity afforded by internet technologies. Community is also central to participatory culture, the study of which began at the cusp of the second media age. This paper critically examines the technocultural formation of online community in the context of fandom and its relationship to specific platforms from Usenet to Tumblr. Based on the analysis of interview data collected from participatory fans (n = 33), I argue that not all platforms enable community formation. While the participants had a sense of community as members of listservs, Yahoo groups and LiveJournal, the same was not true of Facebook, Twitter and Tumblr, even though they afforded a number of fannish pleasures. These findings raise questions as to the ongoing centrality of online community in the late second media age.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0050.010
Scholarly communication0.0070.006
Open science0.0000.004
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 head0.101
GPT teacher head0.403
Teacher spread0.302 · 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 designQualitative
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".

Quick stats

Citations42
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueConvergence The International Journal of Research into New Media TechnologiesSame topicDigital Games and MediaFrench-language works237,207