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Record W1805162864

Psychotherapist-Patient Privilege, Recordkeeping, and Maintaining Psychotherapy Case Notes in Professional Practice: The Need for Ethical and Policy Reform

2015· article· en· W1805162864 on OpenAlexaffvenueabout
Jon Mills

Bibliographic record

VenueCanadian Journal of Counselling and Psychotherapy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsAdler
Fundersnot available
KeywordsConfidentialityPrivilege (computing)Mental healthSubject (documents)PsychologyPresumptionPublic relationsPsychotherapistLawPolitical scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

A growing trend in Canadian mental healthcare professes that the best standard of practice is to keep complete notes and correspondence of all patient transactions in the mental health practitioner’s file, including a record of intimate personal details revealed in therapy. This file, however, is subject to intrusive inspection by third parties who may ask to view its contents. This creates a conundrum and a potential risk for the field of mental health. Professionals of all kinds are asked to keep in confidence whatever is disclosed in sessions, but the law prohibits privileged communication. This article challenges the distinction between privilege and confidentiality, and discusses the recording and filing of psychotherapy case notes, as well as the greater ethical questions these issues generate. I advocate a corrective: an alternative method of recordkeeping that maintains files for process notes separate from the official clinical record. This procedure insulates the patient and therapist from potential risk of ethical and legal exploitation inherent in our current presumption that all clinical notes and records are subject to disclosure and inclusion in the client’s file. The future of professional policy is at stake for all mental health professionals in Canada unless this issue is addressed.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.073
GPT teacher head0.453
Teacher spread0.381 · 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 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

Citations2
Published2015
Admission routes3
Has abstractyes

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