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Record W4246073019 · doi:10.32920/ryerson.14643840.v1

Jumping on the “brand-wagon”? An Examination of Political Branding in the 2011 Canadian Federal Election

2021· preprint· en· W4246073019 on OpenAlexafffundabout
Zandra Alexander

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsToronto Metropolitan University
FundersMcMaster University
KeywordsPoliticsPolitical communicationPolitical scienceDemocracyFederal electionPublic relationsPhrasePolitical advertisingAdvertisingMedia studiesSociologyLawBusinessLinguistics

Abstract

fetched live from OpenAlex

Political branding is an increasingly prominent term in both the academic and industry realms of political communication. Yet much debate has been waging regarding its viability as a concept of study. Some scholars express concern regarding the impact on democratic discourse and voter engagement, while others question its existence beyond a trendy marketing phrase. Before such questions of impact can be explored in-depth, it is important to first determine if political branding can actually be detected and measured as a truly unique form of political communication. The question of political branding as a measurable form of political communication will be explored through the lens of the 2011 Canadian federal election. The study begins by briefly tracing the historical evolution of political communication in post-war democracies. From there, various definitions of the concept are discussed, before moving to some of political branding’s key features. A multimodal content analysis is preformed on 33 television advertisements from the three major political parties participating in the 2011 Canadian federal election in an attempt to discover if branded qualities are present in the advertising content, and if so, to what extent?

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.288
Teacher spread0.234 · 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

Citations0
Published2021
Admission routes3
Has abstractyes

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