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Record W4362475357 · doi:10.15273/allons-y.v7i0.11478

Providing Chaplain Support to Morally Injured Servicewomen

2023· article· en· W4362475357 on OpenAlexvenueno aff
Daniel L. Roberts

Bibliographic record

VenueAllons-y Journal of Children Peace and Security · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsShameStorytellingPsychologyMoralityEconomic JusticeSocial psychologyNarrativeLawPolitical science

Abstract

fetched live from OpenAlex

The following article may serve as a learning tool for chaplains who are available to provide care to servicewomen suffering from moral injury. Moral injury occurs when someone experiences, takes part in, or witnesses a traumatic event that violates their deeply held beliefs about truth, justice, or morality. Using a gendered approach rooted in feminist principles and research, the text provides a list of traits and attitudes that effective chaplains possess, five principles of support, and recommendations for how chaplains can enact those concepts in specific counseling situations. The five principles of support are: establish trust, enable storytelling, be empathetic and calm, listen for special themes, and offer alternative perspectives. Together, the principles help create an environment in which a military woman can receive vitalizing pastoral care. The article describes in detail the five special themes of disempowerment, sink holes, guilt and shame, loss of identity, and low self-worth and explains how chaplains can offer alternative perspectives so that a woman client might experience post-traumatic growth and recovery.

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)0.003
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 score0.430
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.333
Teacher spread0.313 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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