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Record W4308615637 · doi:10.32920/ryerson.14657517.v2

A matter of choice : a critical discourse analysis of ECEC policy in Canada's 2006 federal election

2022· preprint· en· W4308615637 on OpenAlexaboutno aff
Brooke Richardson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCritical discourse analysisDominance (genetics)Discourse analysisNominalizationNewspaperPoliticsFederal electionHegemonyPolitical scienceRepresentation (politics)SociologyPublic administrationMedia studiesIdeologyLinguisticsLaw

Abstract

fetched live from OpenAlex

This paper used a Critical Discourse Analysis (CDA) to analyze the representation of Early Childhood Education and Care (ECEC) in the 2006 federal election in Canada. Using Fairclough's approach to CDA, the study analyzed written documents including newspaper articles from The Globe and Mail and The National Post, the policy platforms of the Liberal and conservative parties, and political speeches from party leaders. The "choice" discourse was found to be dominant in the majority of texts examined. A dominant discourse is one that is created and sustained by those with power thus contributing to hegemony in society. Three textual and discourse processes were found to legitimize the "choice" discourse and contribute to its dominance: rationalization, nominalization and conversationalization. It is suggested that the language used in public documents throughout this election and the subsequent dominance of the "choice" discourse may have had a significant impact on citizens' understanding and appreciation of the complexities of the ECEC issue.

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)0.016
metaresearch head score (Gemma)0.031
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: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.013
Science and technology studies0.0420.031
Scholarly communication0.0210.005
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.352
Teacher spread0.337 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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