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Record W1981898199 · doi:10.1177/0892020611426894

Timetabling and extracurricular activities: a study of teachers’ attitudes towards preparation time

2012· article· en· W1981898199 on OpenAlexaffabout
Robert F Whiteley, George V. Richard

Bibliographic record

VenueManagement in Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsWorkloadTime allocationMedical educationTime managementPsychologyMathematics educationPedagogySociologyMedicineManagementSocial science

Abstract

fetched live from OpenAlex

Many models of timetabling exist in secondary schools in Western educational jurisdictions. This study examines whether or not teachers teaching a full course load without preparation time during a semester are willing to volunteer to participate in extracurricular activities. This research was conducted in a rural school district in British Columbia, Canada. Teacher workload, preparation time and willingness to volunteer for extracurricular activities were addressed. Over 70 per cent of respondents to the survey indicated that they found their workload unmanageable during the semester in which they had no preparation time while over 90 per cent of respondents indicated they wanted to have preparation time distributed evenly over the full school year. A significant majority of teachers do not supervise extracurricular activities when they have no preparation time. A comprehensive literature review examining advantages and disadvantages of the semester timetable and an extensive bibliography are included.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.024
GPT teacher head0.365
Teacher spread0.340 · 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 designObservational
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

Citations16
Published2012
Admission routes2
Has abstractyes

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