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Record W4402677066 · doi:10.4324/9781032696409

Holistic Ways of Learning at a Community School

2024· book· en· W4402677066 on OpenAlexaboutno aff
Jessica Poff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldComputer Science
TopicEducational Challenges and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMathematics educationSociologyPedagogy

Abstract

fetched live from OpenAlex

This volume provides a critical narrative inquiry into the learning experiences of adults and children at a Community School in Canada. It tells the story of a closely connected family of people living and learning together, combining activities such as learning to read and write with unconventional learning experiences such as trick riding, rodeo competitions, and yoga and meditation practices. Through the lens of holistic education and critical pedagogy, the author draws on interviews with students and teachers at the alternative school, as well as her own autoethnographic experience, to build out a full picture of the experience and dynamics of the school. This critical and holistic schooling narrative aims to explore assumptions about alternative schooling and highlight ways in which modern mainstream schools can be challenged to be different in the post-pandemic era. It will be of interest to scholars, researchers, and postgraduate students with interests in experiential education, alternative education, narrative inquiry, critical theory, and holistic theory.

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)0.001
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: Other
Teacher disagreement score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.019
Scholarly communication0.0090.005
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.183
GPT teacher head0.328
Teacher spread0.145 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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