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Record W1524800924 · doi:10.1111/1745-8315.12315

Unconscious phantasy and its conceptualizations: An attempt at conceptual integration

2015· review· en· W1524800924 on OpenAlexaff
Werner Bohleber, Juan Pablo Jiménez, Dominique Scarfone, Sverre Varvin, Samuel Zysman

Bibliographic record

VenueThe International Journal of Psychoanalysis · 2015
Typereview
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsUnconscious mindEpistemologySituatedPsychologyCognitive scienceComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

That there is a lack of consensus as to how to decide between competing, at times even contradictory theories, and about how to integrate divergent concepts and theories is well known. In view of this situation, the IPA Committee on Conceptual Integration (2009-2013) developed a method for comparing the different versions of any given concept, together with the underlying theories and fundamental assumptions on which they are based. Only when situated in the same frame of reference do similarities and differences begin to appear in a methodically comprehensible and reproducible form. After having studied the concept of enactment followed by the publication of a paper in this Journal in 2013, we proceeded to analyze the concept of unconscious phantasy while at the same time continuing to improve our method. Unconscious phantasy counts among the central concepts in psychoanalysis. We identified a wide range of definitions along with their various theoretical backgrounds. Our primary concern in the present paper addresses the dimensional analysis of the semantic space occupied by the various conceptualizations. By way of deconstructing the concepts we endeavoured to establish the extent to which the integration of the different conceptualizations of unconscious phantasy might be achieved.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.907
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.136
GPT teacher head0.467
Teacher spread0.331 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations28
Published2015
Admission routes1
Has abstractyes

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