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Record W2115688603 · doi:10.1177/00030651060540031401

Medication as Object

2006· article· en· W2115688603 on OpenAlexaff
Adele Tutter

Bibliographic record

VenueJournal of the American Psychoanalytic Association · 2006
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsColumbia College
Fundersnot available
KeywordsObject (grammar)Representation (politics)PsychologyMeaning (existential)Agency (philosophy)Object relations theoryDyadAction (physics)IntentionalityResistance (ecology)EpistemologySocial psychologyCognitive scienceComputer scienceArtificial intelligencePsychotherapistPsychoanalytic theory

Abstract

fetched live from OpenAlex

People experience and treat medication as though it were a person: in other words, as an object. Among the many symbolic meanings attributed to medication, this sort of personification, or object representation, is a meaning that medication is uniquely positioned to contain and convey: imbued with intentionality and influence, medication moves beyond the sphere of static, iconic representation and enters the changeable, dynamic object world of action, aim, and agency. Unlike more generic or stereotypic meanings, object representations attributed to medication may reflect the patient's specific dynamics and object relations. These representations are many and mutable, and take on shifting and overlapping forms that evolve with the analytic process. Medication may represent a third person within the framework of an analytic treatment, expanding the analytic dyad into a triad and offering new transference paradigms to explore. The defensive displacement of transferential qualities and attitudes, or split-off parts thereof, from the analyst onto medication can serve as a powerful resistance to the awareness of the transference to the analyst. Clinical examples illustrate the utility and importance of the analysis of medication as object, for both patient and analyst, with particular attention to the transference.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
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 science0.0000.000
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 head0.007
GPT teacher head0.273
Teacher spread0.266 · 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

Citations33
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Psychoanalytic AssociationSame topicPain Management and Placebo EffectFrench-language works237,207