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Record W2953589447 · doi:10.22329/csw.v6i2.5669

Using Bio-Spiritual Music Focused Energetics for Social Workers to Enhance Personal Identity and Professional Transformation: The Power of Self-Reflective Empathy

2019· article· en· W2953589447 on OpenAlexaffvenueabout
Wilfred Gallant, Michael J. Holosko, Melanie D. Gallant

Bibliographic record

VenueCritical Social Work · 2019
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAddictionPsychologyEmpathySocial workIdentity (music)Power (physics)Professional developmentCertificationAffordancePersonal developmentMedical educationPsychotherapistSocial psychologyPedagogyMedicineManagementPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Working conditions, client demands, heavy workloads, and numerous other factors cause high levels of stress among social workers and undermine their potential for self-fulfilment and productivity. Bio-Spiritual – Music-Focus - Energetics (BSMFE) is a focusing technique used in this study for social workers and addiction counsellors as a part of staff training and development and re-certification. This article speaks to the need for creative and uniquely supportive approaches for helping professionals. It presents an account of addictions counsellor training and education (N=7) in Windsor, Ontario, Canada. During a day long workshop, social workers and counsellors participated to heighten their awareness of their own inner-directed processes. Implications are directed toward social workers, addiction counsellors, music therapists, helping professionals, clergy, and pastoral counsellors, in their own spiritual quest toward personal fulfilment and professional growth and transformation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.429
Teacher spread0.361 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2019
Admission routes3
Has abstractyes

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