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Record W4220745338 · doi:10.3138/jmvfh-2021-0062

Living separately during the week: Influences on family functioning, health, and well-being of UK naval families

2022· article· en· W4220745338 on OpenAlexvenueno aff
Rachael Gribble, Nicola T. Fear

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthStressorPsychologyNavyAffect (linguistics)Software deploymentFamily lifePhysical healthFamily healthWell-beingGerontologyDevelopmental psychologyMedicineClinical psychologyPsychiatryGeographySociologyNursing

Abstract

fetched live from OpenAlex

LAY SUMMARY Military life can involve many different separations from family as a result of operational demands. Approximately 4 in 10 UK Royal Navy and Royal Marine families report living separately during the week. Although much research focuses on deployment, little research focuses on how these shorter, more frequent, and ongoing separations influence family functioning and the health and well-being of partners, children, and young people. In this study, interviews and focus groups with partners and adolescents in UK naval families found that limitations on time as a family and family dynamics, including roles and relationships, had a negative influence on family functioning. Stressors from these experiences were reported to negatively affect family health and well-being, with poorer mental and physical health among partners and emotional and behavioural difficulties among children. These findings highlight similarities and differences between weekly separations and operational deployments and the need for more research on different types of family separation in the military.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.042
GPT teacher head0.368
Teacher spread0.326 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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