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What’s Missing from this Picture?

2004· book-chapter· en· W2478411775 on OpenAlexaboutno aff
Daniel M. Ogilvie

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyHistory

Abstract

fetched live from OpenAlex

Abstract Both J. M. Barrie and Carl Jung, at critical times in their development, experienced such traumatic discrepancies between their internal self-with-mother representations and what reality suddenly presented them that they scrambled to somehow restore conditions (or cues) that had previously evoked a sense of (subjective) self-continuity and thereby calm disturbances in their internal milieus. In both cases, the most familiar, prominent, and reassuring cue associated with core self safety was the mother. Restorative efforts were required on the parts of both young boys, and Jung had to look outside his home. Chapter 17 described three restorative strategies. One is to endeavor to get the external world to adjust itself in ways that conform to one's internal pictures of a safe environment. J. M. Barrie specialized in that choice. Another avenue for restoring earlier conditions of intersubjective harmony involves giving up all hope of getting the “real world” to behave itself and instead inventing an “imaginary world” that would do the trick. Carl Jung selected that path. A third option, one that is not necessarily independent of the other two, is based on the non-conscious fantasy that if one were to succeed in recreating the feelings of earlier sensations of oneness, new life would magically be brought to the imprints etched into working models of former glorious times. This chapter begins with a discussion of the first strategy: the attempt to modify features of the external world in ways that fit previously encoded internal pictures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0070.011
Open science0.0010.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0240.003

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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2004
Admission routes1
Has abstractyes

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