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Record W2947591593 · doi:10.25316/ir-1401

Sponsorship of extracurricular activities and the happiness of educators

2018· dissertation· en· W2947591593 on OpenAlexaboutno aff
Dylan Kaye Sharpe

Bibliographic record

VenueVIURRSpace (Vancouver Island University) · 2018
Typedissertation
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessExtracurricular activityPedagogyPsychologyPolitical scienceMathematics educationSocial psychology

Abstract

fetched live from OpenAlex

Academic scholarship had not extensively investigated whether sponsoring, coaching, or leading (sponsoring) school based extracurricular activities (ECAs) influenced the sense of happiness experienced by educators. The present author hypothesized that extracurricular activity (ECA) sponsorship would lead to an increase in an educator’s sense of emotional happiness with their school community. The existing thesis’ author proposed the following research question: To what degree, if any, does sponsoring ECAs in an elementary school setting increase an educator’s sense of happiness? Within the current thesis, a thematic literature review examined influences on educator wellness, barriers to sponsoring, and the benefits of extracurricular activities for educators. Hills and Argyle’s (2002) Oxford Happiness Questionnaire (OHQ) provided measures of happiness to test the existing hypothesis. An anonymized, five-member sample, consisting of an unknown combination of teachers, vice principals, and principals (educators) from Nanaimo-Ladysmith School District 68 (SD68), completed the OHQ before, and after, a minimal six-week period of ECA sponsorship. The mean for the existing sample’s OHQ responses statistically verified that sponsoring ECAs had not increased the sample’s sense of happiness. Supplementary statistical data analyzed from the sample’s OHQ responses corroborated that the present study had resulted in a null hypothesis. Research errors made by present author have limited the existing study’s implications and contributions relating to academic scholarship.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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 designTheoretical or conceptual
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
Published2018
Admission routes1
Has abstractyes

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