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Record W2032183206 · doi:10.1080/14729679.2014.949807

The place and approach of outdoor learning within a holistic curricular agenda: development of Singaporean outdoor education practice

2014· article· en· W2032183206 on OpenAlexaff
Matthew Atencio, Yuen Sze Michelle Tan, Susanna Ho, Chew Ting Ching

Bibliographic record

VenueJournal of Adventure Education & Outdoor Learning · 2014
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOutdoor educationContext (archaeology)PedagogySociologyValue (mathematics)Exploratory researchProfessional developmentPlace-based educationEnvironmental educationGeographySocial science

Abstract

fetched live from OpenAlex

This paper details the potential contribution of outdoor education (OE) in Singaporean education given the recent raft of national curricular reforms aimed at fostering holistic and exploratory learning opportunities. In this context, we contend that increasing recognition of the value of OE, both internationally and locally, heralds specific challenges within unique Singaporean educational conditions that must be taken into account for this subject area to flourish. In particular, we seek to distil the ways in which local community, cultural and school conditions signal the need for a more place-based and contextualised version of OE. Our analysis further addresses the need for adequate professional development frameworks to be installed in order to enhance existing local teachers’ capacities to substantially educate pupils through the outdoors, within a Southeast Asian urban context.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.006
Scholarly communication0.0040.002
Open science0.0010.007
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.343
Teacher spread0.326 · 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 designQualitative
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

Citations20
Published2014
Admission routes1
Has abstractyes

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