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Record W1502186427 · doi:10.22230/cjc.2012v37n2a2472

Canadian Political Consultants’ Perspectives about Political Marketing

2012· article· en· W1502186427 on OpenAlexafffundvenueabout
Jennifer Lees‐Marshment, Alex Marland

Bibliographic record

VenueCanadian Journal of Communication · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsMemorial University of Newfoundland
FundersMcGill University
KeywordsPoliticsDemocracyPolitical communicationPolitical sciencePublic relationsQualitative marketing researchAmerican political scienceMarketingSociologyInfluencer marketingPublic administrationMarketing managementBusinessRelationship marketingLaw

Abstract

fetched live from OpenAlex

ABSTRACT This research in brief explores Canadian political consultants’ practices in political marketing, exploring whether they are, as democratic critiques of marketing often argue, encouraging politics to become poll-driven, and whether they fit into previous international studies on consultants in other countries, especially the United States. Drawing upon qualitative data collected from interviews with key practitioners in Canada and from Canadian news sources, it considers how political consultants utilize market research, communication, and strategy. It also considers the potential impact of the use of political consultants on politicians’ decisions and leadership. It concludes that Canadian political marketing does not fit into an idealistic, realistic, or cynical view of political marketing but is a more complex synthesis and thus the democratic impact is more varied and debatable.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.146
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0460.025
Scholarly communication0.0210.004
Open science0.0020.005
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0100.001

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 head0.031
GPT teacher head0.318
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2012
Admission routes4
Has abstractyes

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