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Record W4385241860 · doi:10.1080/14779757.2023.2234966

Changing emotion with emotion

2023· article· en· W4385241860 on OpenAlexaff
Leslie S. Greenberg

Bibliographic record

VenuePerson-Centered & Experiential Psychotherapies · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyEmotion workAffect (linguistics)Affective scienceCognitive psychologyEmotion classificationSocial psychologyDevelopmental psychologyCommunication

Abstract

fetched live from OpenAlex

This paper provides an overview of an Emotion Focused theoretical framework of human functioning based on the primacy of affect. This is followed by a brief review of the fundamental principles of Emotion Focused Therapy practice. A survival and growth tendency is seen as the main human motivational system, and emotion is seen as in-born and evolutionarily developed, to promote survival and growth. Emotion is seen as more basic than motivation, and therefore more fundamental than either the actualizing tendency or an attachment motive. The latter motivations are both seen as being driven by emotion. Having discussed the nature of emotional functioning the paper concludes by discussing principles of emotional change, and how to work with emotion to change emotion.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.002

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 head0.058
GPT teacher head0.338
Teacher spread0.280 · 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
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

Citations11
Published2023
Admission routes1
Has abstractyes

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