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How Long? How Many? How Much? Evidence of Convergent Validity Among Thin-Slice Behavioral Coding Metrics

Nora A. Murphy et al.

Journal of Nonverbal Behavior2025https://doi.org/10.1007/s10919-025-00489-warticle
AJG 2
Weight
0.44

What the paper says

Despite the ubiquity of thin-slice coding for behavioral measurement, there exists relatively little systematic research into the convergent validity of thin-slice coding metrics for nonverbal behaviors when using human coders. This study utilized five previous datasets to measure four commonly-measured nonverbal behaviors (gaze, gestures, nods, smiles) using three different coding metrics (duration, frequency, rating) coded in 2 or 3 min slices. Convergent validity was measured by comparing a given behavior coded with at least two different metrics. Meta-analytic assessments across studies, behaviors, and metrics indicated strong convergent validity for various metrics for each behavior. Results provide confidence to researchers on the validity of using these thin-slice coding metrics for nonverbal behaviors.

3 citations

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https://doi.org/https://doi.org/10.1007/s10919-025-00489-w

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@article{nora2025,
  title        = {{How Long? How Many? How Much? Evidence of Convergent Validity Among Thin-Slice Behavioral Coding Metrics}},
  author       = {Nora A. Murphy et al.},
  journal      = {Journal of Nonverbal Behavior},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s10919-025-00489-w},
}

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How Long? How Many? How Much? Evidence of Convergent Validity Among Thin-Slice Behavioral Coding Metrics

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.