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“Take Back Your Time”: Facilitating a Student Led Teach-In

2008· article· en· W2563381777 on OpenAlexaboutno aff
Linda A. Heyne

Bibliographic record

VenueSCHOLE A Journal of Leisure Studies and Recreation Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOverworkRecreationPovertyLeisure timeProcess (computing)Event (particle physics)PedagogyPublic relationsPsychologySociologyPolitical scienceMedical educationMedicineComputer sciencePhysical activityEconomicsLaw

Abstract

fetched live from OpenAlex

“Take Back Your Time” (TBYT) is a movement founded by John De Graaf (2003) that exposes the issues of time poverty and overwork in the United States and Canada. This article features the process whereby undergraduate students study De Graaf's TBYT handbook, discuss its concepts, and organize a student-led TBYT “teach-in” for their college community. Primary learning objectives include (a) increasing students' awareness of the societal issues of time poverty and overwork, (b) increasing students' understanding of how overwork and time poverty can be addressed by recreation and leisure professionals, and (c) identifying ways to reverse the effects of time poverty and help people live healthier, more balanced lives. This learning activity would be suitable for courses in leisure education, program or event planning, current issues, or the foundations of the recreation and leisure profession.

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)0.004
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0030.003
Open science0.0030.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.009

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 head0.143
GPT teacher head0.442
Teacher spread0.299 · 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
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
Published2008
Admission routes1
Has abstractyes

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Same venueSCHOLE A Journal of Leisure Studies and Recreation EducationSame topicTeacher Education and Leadership StudiesFrench-language works237,207