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Record W2014358446 · doi:10.1017/s0008423911000497

Explaining Local Campaign Intensity: The Canadian General Election of 2008

2011· article· en· W2014358446 on OpenAlexaffabout
William Cross, Lisa Young

Bibliographic record

VenueCanadian Journal of Political Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of CalgaryCarleton University
Fundersnot available
KeywordsVictoryNominationPolitical scienceVariance (accounting)DemocracyElectoral systemGeographyPublic administrationHumanitiesWelfare economicsPoliticsEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract. There is considerable evidence that local campaign activity is positively related both to a party's constituency level vote share and to voter participation rates. In this article we consider the degree of variance of local campaign intensity at the constituency level in the Liberal and New Democratic parties in the 2008 Canadian federal election and consider the variables that may explain this variance. Utilizing data collected through a post-election mail-back survey of candidates, we find significant variance in local campaign activity and identify six factors that influence it. These are an objective measure of the local candidate's chance for victory in the constituency, the candidate's subjective view of their chances, whether the candidate was challenged for the local nomination, how involved the candidate is in his/her local community, whether the candidate contested the prior election and whether party notables from outside the constituency campaigned in the riding. Résumé. Les preuves sont considérables au fait que l'activité dans les campagnes locales correspond à la part des votes dans la circonscription électorale ainsi qu'à la participation électorale. Dans cet article nous considérons le degré de variance de l'intensité des campagnes locales des partis Libéral et Nouveau Démocratique durant l'élection fédérale Canadienne 2008 et examinons les données qui expliquent la variation. En utilisant les données recueillies par des questionnaires postélectoraux des candidats retournés par la poste, nous trouvons une variance significative dans l'activité des campagnes locales et nous identifions six facteurs qui l'influencent. Ils sont: une mesure objective des chances de victoire du candidat, l'impression subjective du candidat de ses chances de gagner, si le candidat était mis au défi dans la nomination locale, la participation du candidat dans sa communauté locale, si le candidat avait contesté l'élection précédente, et si les notables du parti en dehors de la circonscription faisaient campagne pour le candidat dans sa circonscription.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.075
GPT teacher head0.319
Teacher spread0.243 · 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 designObservational
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

Citations14
Published2011
Admission routes2
Has abstractyes

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