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Record W2018691386 · doi:10.1177/00030651030510010301

Silent Thoughts, Spoken Wishes: When Candidate Experience of the Supervisor Converges With Patient Fantasies

2003· article· en· W2018691386 on OpenAlexaff
Grace Caroline Barron

Bibliographic record

VenueJournal of the American Psychoanalytic Association · 2003
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsColumbia College
Fundersnot available
KeywordsSupervisorFeelingPsychologySocial psychologyIdentity (music)FantasyPsychotherapistComputer scienceAestheticsManagementPhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

How and why a candidate's private experience of two supervisors emerged in patients' fantasies about them is explored. Four issues are examined in light of two control cases: (1) Patients divide, rather than split, the transference between supervisor and candidate, experiencing both ambivalently. (2) Even a patient with no knowledge of the supervisor's identity may have a fantasy of the supervisor that is congruent with the candidate's experience of the supervisor. (3) When new professional traits emerge in the candidate as he or she identifies with his or her mentor, the patient may attribute them to the invisible person in the room--the supervisor; the patient may intuit and be influenced by the candidate's feelings about the supervisor as well. (4) A patient's fantasies about the supervisor may reflect parallel process in reverse, whereby the patient discerns what is going on between supervisor and candidate through his or her treatment, just as the supervisor reads what is going on between patient and candidate through the candidate's reporting of the treatment. Because the trio is the truth of the training case, it seems fitting and empowering to acknowledge and analyze the role of the supervisor in the patient's mind.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.280
Teacher spread0.271 · 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 designObservational
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
Published2003
Admission routes1
Has abstractyes

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