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Record W3086007980 · doi:10.11575/prism/5246

Between Webs of Obligation: Exploring the Lived Experiences of Mothers Serving in the Canadian Armed Forces

2017· dissertation· en· W3086007980 on OpenAlexaboutno aff
Mercy Yeboah-Ampadu

Bibliographic record

VenueOpen MIND · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsObligationLived experiencePolitical scienceGender studiesSociologyPsychologyLawPsychoanalysis

Abstract

fetched live from OpenAlex

With the increasing participation of women in the work force, the experiences of women in the military have generated interest in the work-family and military family literature. Furthermore, with the diverse composition of military personnel, the Canadian Armed Forces and others militaries are witnessing a growing number of their female population having to mediate between the roles and demands of motherhood and military life. However, the particular experiences of mothers in the military have not been well reflected in the literature. The military institution has unique characteristics that separate it from most other employers because it has a legal mandate that allows institutional needs to supersede those of its members and their families. The Canadian Armed Forces recognizes its impact on family life; however, it has paid little attention to the particular experiences of women as mothers. The knowledge and resources to guide social workers and educators with this client population is limited. The following study is located between the military as a place of work and family. Using interpretive phenomenological approaches, the study explores the lived experiences of ten mothers in the Canadian military as they mediate between multiple webs of obligation arising from their roles and mothers and soldiers.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.194
GPT teacher head0.387
Teacher spread0.193 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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