Negotiating Visibility: Mediating Presence through Zoom Camera Choices in Post-Secondary Students during COVID-19
Bibliographic record
Abstract
Students at a large and socially diverse urban university completed an anonymous survey examining online learning experiences during the COVID-19 pandemic with an emphasis on decisions to keep their cameras on or off during synchronous class. The 505 student respondents used 7-point scales to assess their school performance and everyday life experiences during the pandemic, general classroom values, pre-pandemic and current pandemic experiences, technological proficiencies related to Zoom, and camera on/off attitudes, as well as the online behavior of professors, and the role of social media in their everyday lives. The findings underscored two motivations underlying school engagement. Students could be motivated by a need for belonging involving authentic self-presentation while experiencing the emotional presence of others, and/or be instrumentally motivated by a need to perform well and advance their careers. The importance of professors creating a safe online space to foster a sense of belonging was highlighted. Finally, the findings show that feelings about having one’s camera on or off during online classes are related to everyday social media experiences. The social-emotional and pragmatic aspects of university education are complementary facets of a university experience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".