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Record W2089953776 · doi:10.1080/08865655.2002.9695583

Radio programming: Station format and alternative models of the audience in the U.S.‐Mexico border region

2002· article· en· W2089953776 on OpenAlexvenueno aff
Alfonso Morales

Bibliographic record

VenueJournal of Borderlands Studies · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsnot available
Fundersnot available
KeywordsVariation (astronomy)Citizen journalismTarget audienceRadio programComputer scienceSociologyRadio broadcastingTelecommunicationsPublic relationsBusinessMarketingPolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract The article analyzes the use of radio “classified‐ad” shows for the sale of goods and services. The article finds that in commercial radio, some Spanish language radio stations (SLRS) program communicative opportunities for listeners in the form of “classified‐ad” type shows on a regular basis. The article presents two significant finding: first, that program format decisions are organized by the “model of the audience” that station personnel hold. The SLRSs studied hold a “participatory model” of the audience. The article distinguishes different models of the audience and indicates how the models summarize radio station personnel perspectives and behaviors surrounding program choice. The second finding is that proximity to the U.S./Mexico border produces variation in “classified‐ad” type shows. The local variation (in El Paso, Texas, Tucson, Arizona and Albuquerque, New Mexico) in the organization of these programs is described and explained according to the mutual needs and purposes of the local community and the radio station. The article concludes with a research agenda that flows from this initial investigation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.196

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.074
GPT teacher head0.337
Teacher spread0.263 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2002
Admission routes1
Has abstractyes

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