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Record W3045911600 · doi:10.5014/ajot.2020.74s1-po3510

Eco Therapy and Spirituality in Forensic Mental Health: A Preliminary Outcome Study

2020· article· en· W3045911600 on OpenAlexaboutno aff
Clark Patrick Heard, Jared Scott, Stephen Yeo

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2020
Typearticle
Languageen
FieldPsychology
TopicParanormal Experiences and Beliefs
Canadian institutionsnot available
Fundersnot available
KeywordsConversationSpiritualityMental healthPsychologyPsychotherapistInterpretative phenomenological analysisMental illnessMental health careQualitative researchMedicinePsychiatryAlternative medicineSociology

Abstract

fetched live from OpenAlex

Date Presented 03/26/20 OT and spiritual-care staff supported a weekly group at accessible nature spaces over 12 weeks for forensic mental-health clients (n = 9) in Ontario, Canada. Outcomes were measured qualitatively consistent with interpretative phenomenological analysis. Themes highlighted freedom, connection to nature, unguarded reflection and relaxation, and strengthened human connections. Analysis of eco inputs in supporting mental-illness recovery has been limited; this study supports that conversation. Primary Author and Speaker: Clark Heard Contributing Authors: Jared Scott, Stephen Yeo

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.447

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)0.0000.000

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 head0.180
GPT teacher head0.455
Teacher spread0.274 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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