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Record W7028530410

The experiences of women whose military partners have been diagnosed with Posttraumatic Stress Disorder

2016· dissertation· en· W7028530410 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPosttraumatic stressPsychological resilienceQualitative researchMental healthQualitative analysisStress (linguistics)Lived experience
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study explores the experiences of women whose military partners have been diagnosed with Posttraumatic Stress Disorder. I sought to understand the influences that PTSD had on family and couple relationships and whether resiliency was a factor in the experiences of the women. Six women were interviewed for this qualitative study. From these interviews, 10 themes were developed: 1. Women’s recognition of partner’s PTSD symptoms was not immediate; 2. Women blamed themselves for their partner’s changed behaviour; 3. PTSD caused significant stress to the couple relationship; 4. PTSD affected the family unit; 5. Women bore the burden and took on more responsibility; 6. Women forsake their own needs (personal sacrifice); 7. Women experienced intense negative emotions; 8. Women’s health and well-being was negatively impacted by partners’ PTSD; 9. Women gained new insights and no longer considered themselves responsible for their partner’s illness; 10. Women demonstrated resilience and coping.

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)0.004
metaresearch head score (Gemma)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.007
Scholarly communication0.0030.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.201
Teacher spread0.182 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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