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Record W2054147301 · doi:10.4236/ojn.2014.42015

Education is the key to protecting children against smoking: What parents think and do

2014· article· en· W2054147301 on OpenAlexafffund
Sandra P. Small, Andrea Brennan-Hunter

Bibliographic record

VenueOpen Journal of Nursing · 2014
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Lung Association
KeywordsDevelopmental psychologyPsychologyQualitative researchSocial psychologySociology

Abstract

fetched live from OpenAlex

The purpose of this study was to examine parents’ communication with their children about the topic of smoking. A qualitative descriptive design was used. Twenty-nine parents who lived in rural communities and who had children in kindergarten to Grade 6 were interviewed. The data were analyzed for themes. A large majority of parents communicated with their children about smoking through verbal interaction, using any one of three approaches: discussing smoking with their children, telling their children about smoking, or acknowledging their children’s understanding of smoking. Those parents also had shown disapproval of smoking, which took different forms and varied from explicit messages in their verbal communication to implicit messages in their behaviours. Three parents had not verbally communicated at all with their children about smoking. Overall, the parents’ communication patterns with their children varied in terms of quality and coherence with recommendations in the literature.

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)0.005
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0020.002
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 head0.041
GPT teacher head0.361
Teacher spread0.319 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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