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Record W2088100372 · doi:10.1353/cpp.0.0056

Message Content in Canadian Automotive Advertising: A Role for Regulation?

2010· article· en· W2088100372 on OpenAlex
Lisa Watson, Anne M. Lavack, Christina M. Rudin-Brown, Peter C. Burns, James H. Mintz

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Public Policy · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsTransport CanadaUniversity of Regina
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

The message content of automotive advertising was examined to determine whether automotive advertising is meeting the needs of its stakeholders, and whether there is a need for it to become more highly regulated. A content analysis of 200 Canadian television and print advertisements revealed that 18 percent of ads demonstrate unsafe or aggressive driving, while 25 percent of ads feature safety mentions. Television ads are substantially more likely than print ads to feature unsafe or aggressive driving (27 percent vs. 10 percent, respectively), while TV ads are less likely than print ads to mention safety (21 percent vs. 29 percent, respectively). With nearly $550 million spent annually on Canadian automotive advertising, either industry self-regulation or government-imposed regulation may be needed in order to reduce advertising depictions of unsafe driving.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.028
GPT teacher head0.310
Teacher spread0.282 · 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