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Record W4389001953 · doi:10.1177/18369391231211023

Falling by the “ <i>waste</i> side”: Defining and moving towards educator well-being from the perspective of early childhood educators in Ontario, Canada

2023· article· en· W4389001953 on OpenAlexaffabout
Brooke Richardson, Rachel Vickerson, Nadia Bader

Bibliographic record

VenueAustralasian Journal of Early Childhood · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsSheridan CollegeEducation and Early Childhood DevelopmentMount Saint Vincent University
Fundersnot available
KeywordsEarly childhood educationEarly childhoodContext (archaeology)Perspective (graphical)SociologyEmbodied cognitionPedagogyFace (sociological concept)Value (mathematics)PoliticsWell-beingProject commissioningPublishingPsychologySocial scienceDevelopmental psychologyPolitical scienceEpistemologyLaw

Abstract

fetched live from OpenAlex

It has been well-established that highly gendered, early childhood education workforces face major temporal, material, physical and psychological barriers to being well. This issue is particularly pressing in this political moment: a national childcare policy program is being rolled out for the first time in Canadian history. It is in this context that we take a grounded theory methodological approach, rooted in feminist care ethics, to centre and analyse the voices of early childhood educators in both conceptualising well-being and identifying ideas and strategies for moving closer to it. We suggest that concurrently addressing the material and discussive value of early childhood educators is necessary to disrupt existing social structures that rely on early childhood educator’s exploitation. We conclude that truly dismantling what is and building a something better can only be done when early childhood educators’ voices and embodied experiences are centered in the decision-making process.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.243
Teacher spread0.234 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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