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Volunteered, negotiated, enforced: family politics and the regulation of home smoking

2010· article· en· W1593232664 on OpenAlexaff
Jude Robinson, Deborah Ritchie, Amanda Amos, Lorraine Greaves, Sarah Cunningham‐Burley

Bibliographic record

VenueSociology of Health & Illness · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsBritish Columbia Centre of Excellence for Women's Health
FundersEconomic and Social Research CouncilNHS Health Scotland
KeywordsGrandparentSecondhand smokeNegotiationTobacco controlPoliticsPsychologySmokeSocial psychologyEnvironmental healthDevelopmental psychologyMedicinePolitical sciencePublic healthLawNursingGeography

Abstract

fetched live from OpenAlex

The protection of children from secondhand smoke in their homes remains a key objective for health agencies worldwide. While research has explored how parents can influence the introduction of home smoking restrictions, less attention has been paid to the role of wider familial and social networks as conduits for positive behaviour changes. In this article we explore how people living in Scotland have introduced various home smoking restrictions to reduce or eliminate children's exposure to tobacco smoke, and how some have gone on to influence people in their wider familial and social networks. The results suggest that many parents are willing to act on messages on the need to protect children from smoke, leading to the creation of patterns of smoking behaviour that are passed on to their parents and siblings and, more widely, to friends and visitors. However, while some parents and grandparents apparently voluntarily changed their smoking behaviour, other parents found that they had to make direct requests to family members and some needed to negotiate more forcefully to protect children, albeit often with positive results.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.032
GPT teacher head0.380
Teacher spread0.349 · 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.

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

Citations28
Published2010
Admission routes1
Has abstractyes

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