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Record W2061925875 · doi:10.1207/s15327019eb1602_1

A Re-Visioning of Boundaries in Professional Helping Relationships: Exploring Other Metaphors

2006· article· en· W2061925875 on OpenAlexaff
Wendy Austin, Vangie Bergum, Simon Nuttgens, Cindy Peternelj‐Taylor

Bibliographic record

VenueEthics & Behavior · 2006
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of SaskatchewanUniversity of Alberta
Fundersnot available
KeywordsMetaphorBridge (graph theory)Boundary (topology)Engineering ethicsSociologyProfessional boundariesEthical issuesEpistemologyPsychologyPublic relationsPolitical scienceEngineeringMedicinePhilosophy

Abstract

fetched live from OpenAlex

There are many ethical issues arising for practitioners in what are termed the boundaries of professional helping relationships. In this article, the authors argue that the boundary metaphor is not sufficient for conceptualizing these ethical issues and propose that alternative metaphors be considered. The use of a different metaphor might allow practitioners to re-vision the relationship issues in a more realistic, richer, and holistic way. Those explored here include highway, bridge, and territory. For the authors, it is territory that seems to hold the greatest promise.

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)0.009
metaresearch head score (Gemma)0.014
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0070.038
Scholarly communication0.0080.015
Open science0.0020.008
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0050.000

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 head0.241
GPT teacher head0.429
Teacher spread0.188 · 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

Citations67
Published2006
Admission routes1
Has abstractyes

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