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"The Pure Guidelines of the Monastery Are to be Inscribed in Your Bones and Mind" Dogen (2010, p. 42): Mental Health Nurses'™ Practices as Ritualized Behaviour

2012· article· en· W4400610494 on OpenAlexaffvenueabout
Graham McCaffrey

Bibliographic record

VenueJournal of Applied Hermeneutics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMental healthInterpretation (philosophy)ReflexivityTheme (computing)BuddhismInscribed figureSoulHermeneuticsNursingPsychologySociologyPsychoanalysisMedicineEpistemologyPsychotherapistPhilosophyAnthropologyTheology

Abstract

fetched live from OpenAlex

Forms of practice among nurses on acute care mental health units present a way of revealing how different traditions and values are in play between nurses and also within nurses. This paper represents one interpretive theme from a larger, hermeneutic study of nurses’ experiences of nurse-patient relationships on acute care mental health units, using Buddhist perspectives as a resource for interpretation of interviews with nurses. Understandings of ritual in the Zen Buddhist tradition and Catherine Bell’s (2009a) concept of ritualized behavior enabled an interpretive analysis of nurses’ activities as the expression and reflexive reinforcement of underlying traditions, values, and beliefs. In particular, nurses’ preferences among ways of relating with patients evinced contrasting background traditions of confinement and therapeutically directed engagement.AcknowledgementsNo hermeneutic work belongs wholly to its author, and I wish to acknowledge Dr. Shelley Raffin-Bouchal, my doctoral supervisor, and Dr. Nancy Moules, who was a very active member of my supervisory committee for all their guidance and support in conducting the study from which this paper emerged.A version of this paper was presented by the author at the Canadian Hermeneutic Institute, Halifax, Nova Scotia, May 23, 2012. Â

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.124
GPT teacher head0.435
Teacher spread0.311 · 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".

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Citations0
Published2012
Admission routes3
Has abstractyes

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