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Record W7132973371

Fostering Creativity within Ontario's Neoliberal Education System

2015· other· en· W7132973371 on OpenAlexaboutno aff
Michelle Park

Bibliographic record

VenueTSpace · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityParallelsCITESNeoliberalism (international relations)Creative educationHigher education
DOInot available

Abstract

fetched live from OpenAlex

This study seeks to explore the degree to which the neoliberal ideas embedded in Ontario education shape the way creativity is fostered in high school students. Two high school educators, who teach classes from different ends of the academic spectrum, were interviewed for their experiences and thoughts on characterizing, identifying and assessing creativity in the classroom. The purpose in selecting educators from schools that exhibit high and low academic achievement was to draw parallels with the literature that cites streaming as an outcome of a neoliberal education system. It was found that while participants greatly differed in how they characterized creativity, both supported the notion that nurturing creativity would benefit the growth and success of their students. In the analysis, I concluded that the neoliberal ideals rooted in education policy may influence the way in which creativity is characterized by schools with high achievement, but both participants do not gear their students to become agents for economic prosperity. In the final chapter, I list the implications for the educational community, along with future considerations and further limitations of this study.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.947
Threshold uncertainty score0.932

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.010
Scholarly communication0.0060.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.084
GPT teacher head0.379
Teacher spread0.295 · 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 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
Published2015
Admission routes1
Has abstractyes

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