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Record W2106196715 · doi:10.1177/1046496413487409

Beyond 12 Angry Men

2013· article· en· W2106196715 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSmall Group Research · 2013
Typearticle
Languageen
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsYork University
FundersUniversity of Toronto
KeywordsPsychologyVariety (cybernetics)Group (periodic table)Group dynamicSocial psychologySample (material)Cognitive psychologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

The ability of group members to shape group behaviors can greatly influence collective outcomes; however, the skills associated with correctly recognizing behaviors in situ and responding appropriately to them on a real-time basis are typically not emphasized in group dynamics education. In this article, we describe a pedagogical method that uses film excerpts and a thin-slicing technique specifically designed to help students develop such skills. We identify a variety of sample film excerpts that illustrate several group behaviors—behaviors that recent research suggests can influence group effectiveness in different contexts. We end by discussing which group phenomena may or may not be particularly well-suited to this technique.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.536
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0260.020

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 head0.257
GPT teacher head0.528
Teacher spread0.271 · 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