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Record W2944033854 · doi:10.1177/0022167819847094

Women’s Experiences of Nature as a Pathway to Recovery From Sexual Assault

2019· article· en· W2944033854 on OpenAlex
Ceri Moore, K. Jessica Van Vliet

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Humanistic Psychology · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of AlbertaCentre for Addiction and Mental Health
Fundersnot available
KeywordsRuminationSexual assaultPsychologyNarrativeQualitative researchSocial psychologyPsychotherapistDevelopmental psychologyPoison controlSuicide preventionCognitionMedicineSociologyPsychiatryMedical emergency

Abstract

fetched live from OpenAlex

Given the serious challenges faced by female survivors of sexual assault, an understanding of how they heal after such an experience is vital. Yet little is known about how being in nature may be helpful in this regard. The purpose of this qualitative study was to develop an in-depth understanding of how nature helps women heal from sexual assault. A narrative analysis of semi-structured interview data provided by four female sexual assault survivors generated four main themes. These themes point to how nature served as a source of emotion regulation and spiritual connection, as well as how it facilitated greater acceptance and reduced dissociation. Themes also indicated reduced negative thinking and rumination, and increased attention to the here and now. Findings are contextualized within the existing literature on sexual assault, and implications for counselling and psychotherapeutic practice with survivors are provided.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0140.000

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 head0.028
GPT teacher head0.318
Teacher spread0.290 · 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