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Record W4206123619 · doi:10.1002/9781119591498.ch9

Warm‐Up and Icebreaker Techniques

2021· other· en· W4206123619 on OpenAlexaboutno aff
Rosemary Crouch

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsnot available
Fundersnot available
KeywordsAction (physics)PublishingPsychologyEngineeringArtLiteraturePhysics

Abstract

fetched live from OpenAlex

Adam Blatner (known as Blatner, H. A. (1973). Acting-In Practical Applications of Psychodramatic Methods. New York;: Springer Publishing Company Inc.) is a psychodramatist who also published comprehensive material for warm-up techniques and in this chapter his book ‘Acting In’ is referred to. The warm-up techniques used by a famous Israeli psychodramatist are also described here, developed by Remocker, A. and Storch, E.T. (1977). Action Speaks Louder. Canada: Copyright authors. ‘Action Speaks Louder’ is on every occupational group therapist's book shelf! Some of the techniques described here are also frequently used by Louise Fouché (see Chapter 4). This chapter describes warm-up (icebreaker) techniques that have been tried and tested in numerous groups and are recommended for use by an occupational group therapist. Artistic materials such as paint and clay are often used and the use of music also enhances the techniques.

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: Methods · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0320.008

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 head0.017
GPT teacher head0.317
Teacher spread0.300 · 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
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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