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Record W1515626954 · doi:10.24124/c677/2010185

Campaigning and Digital Media in Alberta: Emerging Practices and Democratic Outcomes?

2010· article· en· W1515626954 on OpenAlexaffvenueabout
Peter J. Chen, Peter Jay Smith

Bibliographic record

VenueCanadian Political Science Review · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsAthabasca University
Fundersnot available
KeywordsDemocratizationDemocracyPoliticsDigital mediaSocial mediaPolitical sciencePublic relationsPolitical economySociologyLaw

Abstract

fetched live from OpenAlex

This article examines the use and impact of an array of established and emerging digital media on the 2008 Alberta provincial election. Based on data collected from a range of methods, we explore the application of digital media by candidates and political parties. In describing the extent to which various forms of digital media were employed as campaign tools, the article examines the role of digital media in overcoming the media access gap between the dominant political party and other oppositional and minor parties (democratization). As a source of comparison, data from the 2008 national election is employed. The article argues that the evidence supporting democratization is weak. Although there are indications that digital media is one area of campaigning that suffers from the lowest performance gap between different political parties and actors, we identify that structural, human and financial factors advantage the dominant parties' access to both conventional and digital media. This appears significant given the electoral success of the incumbent, and the continued decline in voter participation. The inability of digital media to reinvigorate Alberta democracy lies in other factors of which, we argue, politics is but one, historical, social and economic factors being significant as well.

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)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.030
GPT teacher head0.375
Teacher spread0.345 · 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 designTheoretical or conceptual
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

Citations3
Published2010
Admission routes3
Has abstractyes

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