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Record W4285328134 · doi:10.1521/jsyt.2021.40.4.12

Redundant Attempted Solutions: Operative Diagnoses and Strategic Interventions to Disrupt More of the Same

2021· article· en· W4285328134 on OpenAlexvenueno aff
Grégoire Vitry, Claude de Scorraille, Claudette Portelli, Michael F. Hoyt

Bibliographic record

VenueJournal of Systemic Therapies · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)PsychotherapistVignettePsychologyMedical diagnosisMedical prescriptionPsychiatryMedicineSocial psychologyNursing

Abstract

fetched live from OpenAlex

Beginning with the Mental Research Institute (MRI) in Palo Alto, California, a meta-model has been described in which redundant attempted solutions (RASs) are seen to maintain the mental difficulties that they attempt to resolve. Giorgio Nardone and his colleagues at the Centro di Terapia Strategica in Arezzo, Italy, have developed this constructivist approach via a strategic dialogue method that renders an initial diagnostic interview a deliberate and collaborative therapeutic intervention. Using SYPRENE, a systemic practice research network (Vitry et al., 2020), this article presents a reading of persistent psychological problems in terms of the RASs of avoidance and/or control in which they are embedded, and then demonstrates with a clinical vignette how this grid can guide therapeutic prescriptions.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.073
GPT teacher head0.395
Teacher spread0.323 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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