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Record W4239644183 · doi:10.24124/2013/bpgub1049

In relationship: An illustrated autoethnography of counsellor identity development.

2013· dissertation· en· W4239644183 on OpenAlexafffund
C. A. Christie Wittig

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsCanadian HeritageUniversity of VictoriaLibrary and Archives Canada
FundersUniversity of Northern British Columbia
KeywordsAutoethnographyTransformative learningPsychologyIdentity (music)Personal developmentAlliancePerspective (graphical)Qualitative researchDistressPsychotherapistPedagogyMedical educationSociologyAestheticsMedicineGender studiesVisual artsArtPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Counsellors undergo a unique process of identity development. Previous research shows that the therapeutic alliance and the therapists' use of self have greater impact on therapy outcomes than the specific techniques used. Thus, counsellor development involves integrating new skills, knowledge, and theory with a more in-depth knowledge of self and others resulting in a qualitative change in the self of the counsellor. The creation of this blended personal-professional identity is often accompanied by anxiety, insecurity, and distress. Previous research has focused on improvements to educational programs and supervision practices aimed primarily at educators and researchers. This thesis was written by and for the beginning practitioner with the intent of adding a personal dimension to the existing research. Evocative autoethnography was used to explore counsellor development from an affective, relational, and intimate perspective with the hope of both normalizing and celebrating a powerfully transformative experience. --Leaf ii.

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.054
GPT teacher head0.381
Teacher spread0.327 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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