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Transformative Mediation as a Tool for Facilitated Conversations in Intrapersonal and Interpersonal Conflicts

2024· book-chapter· en· W4401937964 on OpenAlexaboutno aff
Marsha Hilton

Bibliographic record

VenueAdvances in human resources management and organizational development book series · 2024
Typebook-chapter
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsIntrapersonal communicationTransformative learningMediationInterpersonal communicationPsychologySocial psychologySociologyPedagogySocial science

Abstract

fetched live from OpenAlex

This study explores the integration of psychological insights into conflict resolution practices in multicultural cities. Through case studies in New York, London, Toronto, and Sydney, the research examines the role of emotional intelligence, cognitive flexibility, and transformative mediation in resolving conflicts. The methodology includes qualitative case study analysis, with data collected through interviews, focus groups, observations, and document analysis. Key findings highlight common themes such as the influence of stress, cultural identity, and facilitated conversations in conflict dynamics. The study underscores the importance of tailored conflict resolution strategies that consider psychological factors and cultural contexts. Implications for future research and practical applications in various settings are discussed, emphasizing the need for continuous adaptation and culturally sensitive approaches in conflict resolution practices.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0060.007
Open science0.0030.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.003

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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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 designTheoretical or conceptual
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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