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Record W2345369195 · doi:10.1177/1527476416644978

My TiVo Thinks I’m Gay

2016· article· en· W2345369195 on OpenAlexaff
Jonathan Cohn

Bibliographic record

VenueTelevision & New Media · 2016
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNarrativeMedia studiesGlobeSociologyIdentity (music)Gender studiesPsychologyAestheticsArtLiterature

Abstract

fetched live from OpenAlex

In 2002, during Silicon Valley’s recovery after the dot-com crash and the recent push for sexual equality in the United States and across the globe, various media began pondering the question of what to do if TiVo “thinks you are gay.” Here, I analyze a King of Queens (1998–2007) episode and a The Mind of the Married Man (2001–2012) episode that center on this question and how they illustrate a sudden breakdown in sexual norms and identities even as they served to make TiVo’s personal video recorders (PVRs) and recommendation systems more attractive to the urban, liberal, and largely heterosexual viewer that TiVo desired. These narratives became deeply connected to TiVo’s identity in ways that made the PVR appear simultaneously transgressive and conventional—the birth of a new algorithmic culture and the furtherance of the television industry as status quo.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.078
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0140.009
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0110.002

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 head0.063
GPT teacher head0.355
Teacher spread0.292 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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