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Record W2728449473 · doi:10.30535/mto.23.2.5

Finding Love in Hopeless Places

2017· article· en· W2728449473 on OpenAlexaff
Marc Lafrance, Lori Burns

Bibliographic record

VenueMusic Theory Online · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsConcordia University
Fundersnot available
KeywordsLyricsMusicalPopular musicVariety (cybernetics)CounterpointInterpretation (philosophy)ScholarshipAestheticsModernityKey (lock)SociologyPsychologyArtVisual artsLiteratureEpistemologyLinguisticsComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This paper presents an interpretive approach to music video analysis that engages with critical scholarship in the areas of popular music studies, gender studies and cultural studies. Two key examples—Pink’s pop video “Try” and Rihanna’s electropop video “We Found Love”—allow us to examine representations of complex human relationality and the paradoxical challenges of heterosexuality in late modernity. We explore Zygmunt Bauman’s notion of “liquid love” in connection with the selected videos. A model for the analysis of lyrics, music, and images according to cross-domain parameters (thematic, spatial & temporal, relational,andgestural) facilitates the interpretation of the expressive content we consider. Our model has the potential to be applied to musical texts from the full range of musical genres and to shed light on a variety of social and cultural contexts at both the micro and macro levels.

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)0.002
metaresearch head score (Gemma)0.007
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0100.016
Scholarly communication0.0090.012
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.067
GPT teacher head0.264
Teacher spread0.197 · 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".

Quick stats

Citations10
Published2017
Admission routes1
Has abstractyes

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