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Record W2558627396 · doi:10.3138/jmvfh.3837

Children's positive experiences growing up in Canadian military households

2016· article· en· W2558627396 on OpenAlexaffvenueabout
Amanda Bullock, Alla Skomorovsky

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsPsychologyFocus groupSoftware deploymentDemographyMilitary personnelDevelopmental psychologyPolitical scienceSociologyEngineeringLaw

Abstract

fetched live from OpenAlex

Introduction: A small body of literature based almost exclusively on US military families suggests that there are positive aspects to growing up in a military household. However, little is known about whether there are positive consequences for children residing in families of the Canadian Armed Forces (CAF). Therefore, the goal of the current study was to examine the positive implications of growing up in CAF households. Methods: Focus groups were conducted with 8- to 13-year-old children ( N=85) from Regular Force CAF families (38 boys, 42 girls, 5 not indicated) across various locations in Canada. Children were asked if they had experienced any positive outcomes from being in a military family, what had been the best thing about having a parent deployed, and what had been the best thing about moving. Results: Children reported some positive aspects of the military lifestyle, such as the opportunity to travel and have new experiences (due to relocations within Canada and abroad) and to develop stronger bonds with their at-home parent during deployment. Discussion: The findings are discussed in terms of ways to foster positive experiences in relation to the military lifestyle.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.572
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.311
Teacher spread0.287 · 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.

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

Citations8
Published2016
Admission routes3
Has abstractyes

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