Predictors of Valid Engagement With a Video Streaming Web Study Among Asian American and Non-Hispanic White College Students
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.
Bibliographic record
Abstract
The study purpose was to determine the predictors of watching most of a Web-based streaming video and whether data characteristics differed for those watching most or only part of the video. A convenience sample of 650 students (349 Asian Americans and 301 non-Hispanic whites) was recruited from a public university in the United States. Study participants were asked to view a 27-minute suicide awareness streaming video and to complete online questionnaires. Early data monitoring showed many, but not all, watched most of the video. We added software controls to facilitate video completion and defined times for a video completion group (≥26 minutes) and video noncompletion (<26 minutes) group. Compared with the video noncompletion group, the video completion group included more females, undergraduates, and Asian Americans, and had higher individualistic orientation and more correct manipulation check answers. The video noncompletion group skipped items in a purposeful manner, showed less interest in the video, and spent less time completing questionnaires. The findings suggest that implementing software controls, evaluating missing data patterns, documenting the amount of time spent completing questionnaires, and effective manipulation check questions are essential to control potential bias in Web-based research involving college students.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it