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Record W167423137

Campus frequencies : the "Alternativeness" of campus radio broadcasting

2008· dissertation· en· W167423137 on OpenAlexfundaboutno aff
Brian Fauteux

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2008
Typedissertation
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBroadcasting (networking)Radio broadcastingMandateCommercial broadcastingEthosRadio programConstruct (python library)TelecommunicationsSociologyMedia studiesPolitical scienceEngineeringComputer scienceLawComputer security
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores the construction of "alternativeness" on Canadian campus radio broadcasting, using the CKUT Radio-McGill program Underground Sounds as a case study. It is the purpose of this thesis to situate campus broadcasting within the contemporary terrestrial broadcasting environment, looking at literature that theorizes and conceptualizes ideas about what makes campus broadcasting alternative from other broadcast forms, and what factors influence and structure the boundaries and limitations of "alternativeness" on campus radio. Included in this topic is an examination of how terms and concepts such as "alternative," "local," "independent," "community," and "scene" are used on campus-community radio programming, and how these terms construct a broadcasting ethos that may or may not be similar to notions of the alternative/independent/local/community in music scenes and identities. The on-air treatment of these terms are juxtaposed to the way they are discussed in the popular music and cultural industries literature. As well, prominent Canadian broadcast history and policy as it relates to campus radio is a significant component of this thesis, particularly its role in shaping the structure and mandate of Canadian campus radio.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.308
Teacher spread0.267 · 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 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

Citations1
Published2008
Admission routes2
Has abstractyes

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