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Healing through self‐reflection

2001· article· en· W2005162804 on OpenAlexaff
Karran Thorpe, Jeannette Barsky

Bibliographic record

VenueJournal of Advanced Nursing · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsChinook Regional HospitalUniversity of Lethbridge
Fundersnot available
KeywordsPsychologySpiritualityPerspective (graphical)DistressNonprobability samplingPersonal developmentReflection (computer programming)Professional developmentNursingMedicinePsychotherapistPedagogyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Today, women have an enlightened view towards their life cycles, which is evidence of their healing potential. Women need to share their insights about their healing potential gained through self-reflective processes. Their voices must be heard so that we can benefit from their collective wisdom. The process of healing through self-reflection has begun as a group of nurses share their insights. Documenting the perspectives of these nurses provides the opportunity for other women to learn from and apply this knowledge to their lives. METHOD: Through purposive sampling, eight registered nurses, all women, were selected to participate in in-depth, personal, semi-structured interviews. The purposes in this paper are to describe a three-stage (i.e. awareness, critical analysis, and new perspective) reflective-thinking model and discuss the application of this model to women's expressed inner knowledge and wisdom across personal and professional life cycles. RESULTS: Three themes, signifying their ability to heal themselves, were labelled: Spirituality, Be-ing Versus Do-ing, and Eustress Versus Distress. CONCLUSIONS: Essentially, self-reflection results from both personal and professional stimuli and signifies the need for change so that healing can begin. Recommendations are offered for nurse educators and researchers.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.328

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 communication0.0000.001
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 head0.053
GPT teacher head0.440
Teacher spread0.387 · 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 designNot applicable
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

Citations32
Published2001
Admission routes1
Has abstractyes

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