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Record W7105534233 · doi:10.20381/ruor-31499

"Pour le bien des enfants?" ("For the Good of the Children?"): Critical News Media Analysis of Deficit Discourses in the Expansion of Quebec's Kindergarten Program in 1960-1962 and 2018

2025· dissertation· en· W7105534233 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsUniversalizationPanacea (medicine)Critical discourse analysisPeriod (music)Psychological resilienceNeoliberalism (international relations)Modernization theoryDiscourse analysisThematic analysis

Abstract

fetched live from OpenAlex

This research project explored historic and current interventionist and deficit-based discourses in news media related to the universalization of kindergarten education in Quebec. Public debates surrounding the universalization of kindergarten for 5-year-olds in the early 1960s, during the Quiet Revolution, a period of rapid modernization and change, were compared to public debates during the 2018 provincial election where the universalization of kindergarten for 4-year-olds was proposed. A series of 196 news articles were analyzed via a critical, intersectional feminist poststructuralist lens, using critical thematic analysis. Themes developed from news media data from the 1960s included topics related to psychological intervention and the normalizing function of kindergarten, views of potentially deficient mothers and their replacement by kindergarten teachers, as well as fears of juvenile delinquency tied to understandings of modernity. From the election period in 2018, themes related to early schooling as a panacea for vulnerability were discussed, as well as shifting discourses tied to motherhood/parenting, the spectre of the "bad mother", and anxieties surrounding Québécois identity and nationhood. Finally, deficit discourses tied to neoliberal influences and human capital theory in early years education were addressed. Similarities and differences between the two time periods were noted, as well as shifts in the inclusion or exclusion of specific voices in public discourse.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.449
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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