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Record W4386597893 · doi:10.1007/s10943-023-01908-2

Towards a Holistic Model of Care for Moral Injury: An Australian and New Zealand Investigation into the Role of Police Chaplains in Supporting Police Members following exposure to Moral Transgression

2023· article· en· W4386597893 on OpenAlexaff
Andrea Phelps, Kelsey Madden, R. Nicholas Carleton, Lucinda Johnson, Lindsay B. Carey, Jean-Michel Mercier, Andrew Mellor, Jeffrey Baills, David Forbes, Peter Devenish‐Meares, Fardous Hosseiny, Lisa Dell

Bibliographic record

VenueJournal of Religion and Health · 2023
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Regina
FundersUniversity of MelbourneAustralian Federal Police
KeywordsMoral injuryHarmMental healthPublic healthCriminologyQualitative researchPsychosocialPsychologyPsychological interventionPublic relationsNursingSociologySocial psychologyPolitical scienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

Police members can be exposed to morally transgressive events with potential for lasting psychosocial and spiritual harm. Through interviews with police members and police chaplains across Australia and New Zealand, this qualitative study explores the current role that police chaplains play in supporting members exposed to morally transgressive events. The availability of chaplains across police services and the close alignment between the support they offer, and the support sought by police, indicates they have an important role. However, a holistic approach should also consider organizational factors, the role of leaders, and access to evidence-based treatment in collaboration with mental health practitioners.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.926

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 studies0.0000.000
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 head0.162
GPT teacher head0.468
Teacher spread0.306 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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