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Record W4317369568 · doi:10.3138/9781487551568

Taoism, Teaching, and Learning

2022· book· en· W4317369568 on OpenAlexafffund
J. Philip Miller

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2022
Typebook
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsECW Press (Canada)University of Toronto
FundersOntario Arts CouncilGovernment of CanadaGovernment of Ontario
KeywordsTaoismMathematics educationComputer sciencePsychologyHistoryArchaeology

Abstract

fetched live from OpenAlex

A Nature-Based Approach to EducationThe ancient Chinese philosophy of Taoism contains profound wisdom about the cosmos, nature, human life, and education.Taoism seeks to be in harmony with nature, and using it as a guide can help us live in a way that is healing to both ourselves and the planet.Taoism, Teaching, and Learning identifies key aspects of Taoist thought and highlights how these principles can promote a holistic approach to teaching and learning.In particular, this book offers educators guidelines and pedagogical examples for how to instil a perspective of interconnectedness into their classrooms.It sheds light on how philosophical Taoism articulates a vision of the universe and life that mirrors the actual realities of nature.Providing frameworks and methods for teaching and learning based on the interconnectedness of life, Taoism, Teaching, and Learning develops an inspiring vision for education and helps us to see our world in a deeply holistic and meaningful way.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.954
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.231
Teacher spread0.210 · 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.

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

Citations4
Published2022
Admission routes2
Has abstractyes

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