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Record W1252692582 · doi:10.7202/1029423ar

Ontario Kindergarten Teachers’ Social Media Discussions About Full Day Kindergarten

2015· article· en· W1252692582 on OpenAlex
Meghan Lynch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNetnographyCurriculumQualitative researchExploratory researchPedagogyPsychologySocial mediaClass (philosophy)Mathematics educationEarly childhood educationSociologyMedical educationPolitical scienceMedicineSocial scienceComputer science

Abstract

fetched live from OpenAlex

This exploratory netnographic study describes how a sample of Ontario kindergarten teachers perceives the new Ontario Full Day Kindergarten (FDK) curriculum. Discussions from teacher message boards, the comment sections of online news articles, and interviews with kindergarten teachers were analyzed and coded using a qualitative approach. Analysis revealed three major themes: 1) Class size concerns, 2) Team teaching concerns, and 3) Play-based curriculum concerns. Results are in broad agreement with those reported in existing research into Ontario’s FDK initiative. Findings highlight the need for further research with educators involved in Ontario’s FDK and also contribute to the burgeoning field of netnography research. Suggestions for future research and practice are included.

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.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.339
GPT teacher head0.412
Teacher spread0.072 · 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