Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".