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Record W2154878536 · doi:10.20381/ruor-3537

Tuning In to a Hit Parade Pedagogy

2014· dissertation· en· W2154878536 on OpenAlexfundno aff
Brian S. R. Kom

Bibliographic record

VenueuO Research (University of Ottawa) · 2014
Typedissertation
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsnot available
FundersUniversity of Ottawa
KeywordsParadeCurriculumLyricsSociologyImprovisationCritical pedagogyPedagogyMusic educationArtVisual artsMedia studiesLiteratureArt history

Abstract

fetched live from OpenAlex

Contemporary popular music is a ubiquitous social, cultural, and pedagogical force. Enabled by ever-evolving and -expanding technology, its songs and lyrics are transmitted into our most public and private spaces. For this study, I present the Billboard music charts as a functioning pedagogy and curriculum. Riffing on Richter’s denkbilder, Aoki’s curricular worlds of plan and lived experience, Giroux’s public pedagogy, and Giroux & Simon’s theorizing on youth culture, I sound out messages and motives embedded within the hit parade pedagogy. DJing a methodology of qualitative inquiry, autoethnography, and free association, I listen closely to chart-topping songs by Lady Gaga, Katy Perry, and P!nk that feature themes of marginalization, and consider the paradox presented by the juxtaposition of their popularity and subject matter. I suggest that this playlist legitimizes and perpetuates its listeners’ marginalization, running counter to its supposed intent to galvanize and inspire. Before signing off, I consider the implications for school-based educators and pedagogy in regard to engaging marginalization, particularly the notion of implementing a curriculum with which students may participate and sing along.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.667
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.000

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 head0.083
GPT teacher head0.325
Teacher spread0.241 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2014
Admission routes1
Has abstractyes

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