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Record W1919544060 · doi:10.18357/ijcyfs34201211486

FAMILY PROBLEM-SOLVING: HOW DO FAMILIES WITH ADOLESCENTS MAKE DECISIONS?

2012· article· en· W1919544060 on OpenAlexvenueno aff
Luisa Molinari, Marina Everri

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2012
Typearticle
Languageen
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyTask (project management)PsychologySurrenderSocial psychologyDevelopmental psychologyGeographyMedicineEngineering

Abstract

fetched live from OpenAlex

In the present study, we adopt an observational method for the analysis of family members’ interactions during a problem-solving task. The specific focus of our work is to put the family as a whole beneath the lens of observation, as well as to analyze how the parents and the adolescent separately contribute to the task solution. Twenty-eight non-clinical families with adolescents (13 to 16 years old) were filmed in their homes during a problem-solving task. Family interactions were analyzed according to four observational measures: family efficiency, family communication, family climate, and family participation. Three different patterns of family decision-making are described: families that control (high efficiency, calm family climate, collaborative participation), families that surrender (low efficiency, tense family climate, individual participation), and families that struggle (intermediate efficiency, serious family climate, alternated participation). Theoretical and practical implications in terms of everyday ways of dealing with problems in families with adolescents 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 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)0.002
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.061
GPT teacher head0.356
Teacher spread0.295 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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