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Record W4292937826 · doi:10.17760/d20412696

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2021· dissertation· en· W4292937826 on OpenAlexaboutno aff
Nicole Willard

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsClubProfessional developmentJournal clubAction (physics)Identification (biology)Early childhoodMedical educationPublic relationsPolitical sciencePedagogyAction researchPsychologyMedicine

Abstract

fetched live from OpenAlex

Barriers to professional development can negatively impact educators' ability to participate. The purpose of this action research study was to investigate the role of an early childhood education (ECE) book club in ameliorating challenges to participation in professional development in a childcare center in Ontario, Canada. Data collected in Cycle 1 included interviews with 6 educators from a childcare center near Boston, Massachusetts. Cycle 2 action steps were designed, implemented, and evaluated to provide educators with support through the implementation of a virtual professional development book club. The study concluded that an educator's place of employment has a large impact on the barriers they face to engaging with professional development. For some educators, the removal of external barriers, like limited time and money, may not be able to help them overcome internal barriers, like lack of motivation. The study also found that relationships both within and outside of the book club may influence participant experiences. Implications for the organization included identification of barriers facing early educators to participating in professional development, a gained understanding of how to assess the effectiveness of the book club, and an assessment of the role that the book club played in developing teacher leadership.--Author's abstract

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.404
Threshold uncertainty score0.851

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.4040.130

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 head0.047
GPT teacher head0.427
Teacher spread0.380 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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