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Record W4403965404 · doi:10.4324/9781003536246

A Shimmering Landscape

2024· book· en· W4403965404 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldPsychology
TopicJungian Analytical Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsAstrobiologyGeographyBiology

Abstract

fetched live from OpenAlex

Acclaimed Winnicott scholar Dodi Goldman offers an intriguing account of the psyche’s work of imaginative elaboration. Why does the world feel one way when we are imaginatively alive to it and quite another when we are not? How does one both imagine and see things as they are? What happens when we cannot do so? This book creatively explores the interplay between the imaginative and actual in psychoanalysis and life. Each chapter centers around an evocative visual image—a prehistoric figurine, a Hindu lithograph, an Italian etching, an Inuit statue, a painting by Magritte, and more—to reveal unexpected connections and novel insights into what enlivens experience to make the personal landscape shimmer. With a fresh and delightfully playful approach, this volume is essential reading for psychoanalysts, psychotherapists, humanities scholars, and anyone curious about the fragile alliance between the imaginative and actual in human experience.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.007
Scholarly communication0.0050.005
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.031
GPT teacher head0.345
Teacher spread0.313 · 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
Published2024
Admission routes1
Has abstractyes

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