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Record W2967175990

A Situational Analysis of Municipal Early Childhood Education Policy Documents

2019· article· en· W2967175990 on OpenAlexaboutno aff
Maureen Cullen

Bibliographic record

VenueScholarship@Western (Western University) · 2019
Typearticle
Languageen
FieldComputer Science
TopicEducational Systems and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceSituation analysisPublic relationsPsychologyPublic administrationEconomicsManagement
DOInot available

Abstract

fetched live from OpenAlex

Studies have been conducted at the provincial and federal levels that expose dominant discourses in child care policy documents and reports. However, there has not been a similar examination of documents at the municipal level. This study uses a qualitative situational analysis to investigate discourses that are present in municipal documents of a mid-size Ontario city as they pertain to the child care sector. Drawing on Foucault’s concept of discourse, this study interrogates the discursive functions that dominant ideas might have on policies that inform funding, programming, and subsidies. Through a cartographic exercise of map making, this study reveals and interrogates discourses present in these policies. Three major themes emerge and act to maintain power relations and the self-governance of subjects through compliance. Relatedly, the study also shows how children’s and educators’ voices are missing from policy in any meaningful way and highlights whose voices are heard.

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)0.006
metaresearch head score (Gemma)0.013
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 score0.184
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.017
Science and technology studies0.0100.006
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.324
Teacher spread0.282 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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