Bibliographic record
Abstract
Abstract Campus radio falls under the ‘community’ sector of Canada’s broadcasting system alongside the public and commercial sectors. Campus radio evokes a notion of ‘alternativeness’ in order to indicate its role as a sector rooted in a local community and to define its programming as distinct from other stations. This article uses Underground Sounds, a campus radio show broadcast by McGill University’s CKUT-FM, to explore the construction of ‘alternativeness’ in campus radio programming. This ten-week analysis of Underground Sounds took place in early 2008 and focuses on the artists and songs featured, the interviews conducted by the show’s host and on-air discussion of the show’s role in relation to the Montreal music scene. The findings highlight how ‘alternativeness’ is conveyed but also demonstrate its limitations and boundaries. For instance, new albums and upcoming concert dates factor into setting the limits of ‘alternativeness’, as being of current relevance significantly increases the chances that an artist is programmed. However, programmed artists are predominately represented by independent labels and are often local bands without much financial support. The goal of this article is to consider how ‘alternativeness’ might be conceptualized in relation to campus radio and the programming of ‘local’ and ‘independent’ music.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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.
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".