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Record W2766233133 · doi:10.1111/jftr.12243

Do Changes to Family Structure Affect Child and Family Outcomes? A Systematic Review of the Instability Hypothesis

2018· review· en· W2766233133 on OpenAlexaff
Kristin Hadfield, Margaret Ann Amos, Michael Ungar, Julie Gosselin, Lawrence H.Ganong

Bibliographic record

VenueJournal of Family Theory & Review · 2018
Typereview
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsMemorial University of NewfoundlandDalhousie University
Fundersnot available
KeywordsPsychologyAffect (linguistics)Developmental psychologyMediationInclusion (mineral)Longitudinal dataVariety (cybernetics)Stress (linguistics)Clinical psychologySocial psychologyDemography

Abstract

fetched live from OpenAlex

Many children experience multiple family transitions as their parents move into and out of romantic relationships. The instability hypothesis is a stress mediation model that suggests that family transitions cause stress and that this stress leads to worse developmental outcomes. We conducted a systematic review to evaluate the evidence base for this hypothesis. Thirty‐nine articles met the inclusion criteria. Most reports were secondary analyses of American longitudinal data sets. The support for the instability hypothesis was mixed, with many studies finding no evidence, or evidence only for certain groups, types of transitions, or outcomes. Protective factors and processes that prevent transitions from being stressful may explain some of the variability. Results suggest the need to empirically and theoretically differentiate relationship formation from dissolution, to examine effects of fathers' transitions, to include more and different types of outcomes, and to conduct this research within a broader variety of contexts.

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)0.008
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0070.007
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.068
GPT teacher head0.358
Teacher spread0.290 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations113
Published2018
Admission routes1
Has abstractyes

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