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Record W2010612997 · doi:10.1080/21507686.2010.546865

Considerations for a discourse of collaboration in counseling

2011· article· en· W2010612997 on OpenAlexaffabout
Tom Strong, Olga Sutherland, Ottar Ness

Bibliographic record

VenueAsia Pacific Journal of Counselling and Psychotherapy · 2011
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsUniversity of GuelphUniversity of Calgary
Fundersnot available
KeywordsPsychologySocial psychologyKnowledge managementComputer science

Abstract

fetched live from OpenAlex

Abstract In this paper we consider a discourse of collaborative counseling practice drawing from developments in discourse and social constructionist theory. Collaboration, as we shall refer to it, speaks to negotiating and hopefully sharing initiatives, knowledge and judgment in counselor–client dialogues. However, such negotiations and sharing occur within perceived constraints associated with institutional and professional accountabilities, and are related to unequal powers seen as exercisable by clients and counselors. With these possibilities and constraints in mind, we articulate a discourse of collaborative practice based on counselors and clients sharing content and process expertise in areas often considered the sole prerogative of the counselor. Keywords: collaborationdiscoursecounseling Notes †This was a background paper for a presentation given at the Canadian Psychological Association Conference, Montreal, 11 June 2009. Inspirations from Tom Andersen, John Shotter, Ken Gergen and Harlene Anderson. 1. 'Discursive', as we will use the term, concerns people's use of language (both process- and content-related aspects of such use). It signifies attention to people's use of language in ways that empower or disempower them in constituting the realities of their experiences and relationships.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.684

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 communication0.0000.000
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 head0.037
GPT teacher head0.335
Teacher spread0.298 · 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".

Quick stats

Citations27
Published2011
Admission routes2
Has abstractyes

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