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Record W7132866355

Using aesthetic and experiential education to promote health in the writing classroom: problems and possibilities

2005· dissertation· W7132866355 on OpenAlexaff
Jessica Sherman

Bibliographic record

VenueTSpace · 2005
Typedissertation
Language
FieldPsychology
TopicMental Health via Writing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExperiential learningAutoethnographyCurriculumAssertionPromotion (chess)Foundation (evidence)
DOInot available

Abstract

fetched live from OpenAlex

This autoethnography uses participant observation, the process of writing, and textual and curriculum research to consider problems and possibilities of applying aesthetic and experiential education theories in a high school writing classroom. Three sub-questions underlie the inquiry: Can experiential and aesthetic education techniques promote health? Can writing be taught using those theories? Should writing be taught in such a way? Health promotion research establishes that an understanding and assertion of one's self is a critical foundation for further healthy development. Pedagogical ideas of aesthetic and experiential education theories that support the promotion of health are presented. The researcher then considers her own experience applying the theories presented to teach writing. These reflections, understood in light of textual and document analysis, lead to a theoretical discussion of what is possible and appropriate to teach in school with regard to writing.

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)0.012
metaresearch head score (Gemma)0.022
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 score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.016
Scholarly communication0.0060.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.461
Teacher spread0.392 · 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
Published2005
Admission routes1
Has abstractyes

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