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Record W2040098463 · doi:10.1002/oti.310

The Influence of Context: A Naturalistic Study of Ugandan Children's Doings in Outdoor Spaces

2010· article· en· W2040098463 on OpenAlexaff
Janet Njelesani, Amy Sedgwick, Jane A. Davis, Helene J. Polatajko

Bibliographic record

VenueOccupational Therapy International · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsMonsanto (Canada)University of Toronto
Fundersnot available
KeywordsObservational studySituatedThematic analysisContext (archaeology)Naturalistic observationPsychologyDevelopmental psychologyFocus groupOccupational therapyNaturalismQualitative researchSocial psychologySociologyGeographySocial scienceEpistemologyAnthropologyMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to explore children's everyday outdoor occupations in context. A naturalistic observational approach was employed to record the observed outdoor occupations of children in Mbarara, Uganda. Thematic analysis, through pattern formation and constant comparative analysis, was used to uncover categories and themes in the data. Patterns emerged from the data revealing two overarching categories containing three themes: 1) types of occupations: play, work and nothing in particular and 2) characteristics of occupational engagement: being in peer groups, having fun and using materials in the environment. The themes reveal that children's occupations are both similar and different across minority and majority world cultures and that children's occupations are contextually situated and flexible in nature. A limitation of the study was that the observational approach made identification of children's ages subjective. Subsequent studies should explore children's experiences of occupational engagement using interviews and focus groups.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.024
GPT teacher head0.360
Teacher spread0.336 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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