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Record W2589824977 · doi:10.1123/apaq.2016-0012

Evaluating Internet-Based Information on Physical Activity for Children and Youth With Physical Disabilities

2017· article· en· W2589824977 on OpenAlexaff
Lauren Tristani, Rebecca Bassett‐Gunter, Sunita Tanna

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsYork University
Fundersnot available
KeywordsThe InternetInclusion (mineral)PsychologyPhysical activityWeb siteWorld Wide WebKnowledge translationContent analysisApplied psychologyComputer scienceSocial psychologyKnowledge managementMedicineSociologyPhysical therapy

Abstract

fetched live from OpenAlex

Parents are an important source of support for facilitating physical activity in children and youth with disabilities (CYWD). Approximately 70% of parents report using the Internet to search for information regarding their children's health. This study examined the theoretical content of physical activity information contained on publicly available Web sites targeting parents of CYWD. Web sites were amassed using Google, a combination of various search terms, and predetermined inclusion criteria. The Web sites were coded and analyzed using the content-analysis approach to the theory of specified persuasive educational communication. Half of the total Web site content targeted knowledge-based information and messages concerning outcome expectancies. Web sites infrequently included messages concerning self-regulation. Furthermore, the majority of the Web sites were accumulated using the generic term disability. This research highlights the gaps between theory and practice, emphasizing the need for better knowledge-translation practices.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.366
Teacher spread0.311 · 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 teacher head, 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

Citations17
Published2017
Admission routes1
Has abstractyes

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