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Record W2915797649 · doi:10.1080/15401383.2019.1577198

Using <i>For Colored Girls</i> as a Creative Way to Help Me Understand How Empathic I Am

2019· article· en· W2915797649 on OpenAlexaboutno aff
Jacqueline A. Conley

Bibliographic record

VenueJournal of Creativity in Mental Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyInterpersonal Reactivity IndexPsychologyRating scaleColoredInterpersonal communicationClinical psychologyDevelopmental psychologyCreativitySocial psychologyPerspective-taking

Abstract

fetched live from OpenAlex

The author of this mixed-method research study explored the use of the movie, For Colored Girls, as a creative way to promote and understand how empathy emerged among 20 masters-level counseling psychology trainees. The trainees viewed two video monologues from the movie For Colored Girls (Perry, 2010) and then completed the Toronto Empathy Questionnaire (TEQ) (as a pre-and posttest measure and empathy self-rating scale), the Interpersonal Reactivity Index (IRI), and several open-ended questions and outcome questions. The findings revealed a statistically significant difference between TEQ pre-and posttest measures and a statistically significant positive correlation between self-rating empathy levels on the IRI subscales. Several themes emerged, and the value of using featured films as a creative activity are discussed.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.124
GPT teacher head0.496
Teacher spread0.372 · 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 designQualitative
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

Citations3
Published2019
Admission routes1
Has abstractyes

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