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Record W15764685 · doi:10.1093/heapro/dah611

A Good Problem Description Is Key

2002· article· en· W15764685 on OpenAlexaboutno aff
George R. Raub

Bibliographic record

VenueQuality progress · 2002
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsnot available
Fundersnot available
KeywordsKey (lock)Computer scienceComputer security

Abstract

fetched live from OpenAlex

Schools are a main setting for health promotion for youth. A qualitative case study was undertaken in an inner-city, Canadian school. It explored factors that enabled and constrained youth in the process of a school-based computer-supported community development (CD) project. Nineteen grade seven and eight students worked with four adult facilitators for 12 weeks. They completed a community assessment, planned and implemented actions to improve their school environment. Data were collected by: youth and adult interviews, participant observation, content analysis of online postings and two surveys. Constant comparison and triangulation from various data sources and methods were used to verify themes. Themes were categorized as intrinsic or extrinsic enabling and constraining factors. Intrinsic enabling factors were youth' s perceptions that they were making a difference, and feeling recognized for and having ownership of their work. Extrinsic enabling factors included flexibility in youth's choice of activities, supportive adults and community members and the use of incentives. Intrinsic constraining factors were the perceived slow pace of the CD process, and difficulties in getting group consensus/decision-making. Extrinsic constraining factors included: school disruptions and schedules, a lack of 'buy-in' from teachers and parents, and resource demands-people and computers. Relationships between these factors are noted. Research and practice implications regarding school-based CD to promote youth resiliency are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.250
GPT teacher head0.505
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

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
Published2002
Admission routes1
Has abstractyes

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