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Record W3198365478 · doi:10.53379/cjcd.2021.86

Therapeutic Resonance Across the Miles

2021· article· en· W3198365478 on OpenAlexvenueno aff
Janet Payne

Bibliographic record

VenueCanadian Journal of Career Development · 2021
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsCommitPerspective (graphical)Variety (cybernetics)Field (mathematics)Focus (optics)PandemicPsychologyEngineering ethicsSociologyCoronavirus disease 2019 (COVID-19)Public relationsMedicineComputer sciencePolitical scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper considers the significance of the theoretical underpinnings behind the counselling practices employed by career counsellors within the current pandemic we are living within today. Faced with new ways of interacting with and building relationships with our clients, counsellors must consider how they build therapeutic resonance and whether or not distance counselling can achieve these same goals. Written from the perspective of a graduate student attempting to commit to a dissertation focus by exploring a variety of theories within the field of career development, this paper ultimately asks the question – is it possible to build a therapeutic relationship with a client when physical proximity is not possible?

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0120.015
Scholarly communication0.0090.008
Open science0.0020.018
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0190.004

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 head0.056
GPT teacher head0.315
Teacher spread0.259 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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