Recreational Programming for Commuting Students
Bibliographic record
Abstract
The purpose of this research study ‘Recreational Programming for Commuting Students’ is to determine if time spent commuting to campus is a large influencer regarding student’s decisions to participate in recreational activities on UBC’s Vancouver campus, or if it is due to communication techniques used. The commuter students being addressed range from a total of zero minutes up to 3 hours each day. The length of these commutes is inclusive of both directions, to and from campus. This population of commuter students was chosen to see if there are large differences in a student’s perception of their ability to manage time, and if that becomes a determinant for students to participate in recreational activities. This research will examine the similarities or difference between these commuting students to see any other varying forms of constraints that students may face. Examples of relevant considerations include time management, social skills, skills to be successful in the activity, money constraints, and sense of inclusion/belonging (MacRae, 2011). Studies show that the average time to commute one way has gone up to about 26 minutes, with many people commuting for much longer, and therefore taking away time where individuals could be active (The Astonishing…, 2016). This research study will send out surveys through email to participants in an attempt to overcome time constraints that had been commented on by participants. These surveys will inquire about students issues within current communication methods among campus, and result in a discussion to determine a possible plan of action to improve these strategies. In researching the issues surrounding communication techniques of recreational programming, a subsequent goal of this study would be to increase recreational participation among commuter students. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".