Undergraduate Students’ Awareness of University of Calgary Community Engagement Initiatives
Bibliographic record
Abstract
Community engagement is a term that is frequently used when discussing social initiatives, however, it can be hard to define as there is no widely agreed-upon definition for the term. In general, community engagement is a broad term that encompasses various activities and has different definitions depending on the context of its use. Previous studies have found that students who participate in regular community engagement often experience benefits in different areas of their lives as a result. The University of Calgary has implemented a program called Eyes High, which focuses on improving several aspects of campus life including community engagement. The purpose of this study is to obtain perspectives on community engagement from University of Calgary undergraduate students, and to analyze and compare to the university’s own priorities. Opinion mining will be conducted through crowd-sourcing. Crowd-sourcing is an emerging information obtaining method that has the potential to gather opinions using online/social media platforms. An online survey has been created through Qualtrics, to assess undergraduate students’ knowledge of University of Calgary community engagement initiatives and their perception of and attitudes towards community engagement on campus. We intend to recruit participants through social media pages for UCalgary undergraduates. Furthermore, posters with the QR code for the survey will be put up in various locations around the campus. Participants could scan the QR code to access the survey instantly, or take a picture of the QR code to complete the survey on their own time. Faculty members will be requested to further disseminate the survey invitation through their channels. While this study is a work in progress, we anticipate that results of this survey will allow us to gauge undergraduate students’ awareness of University of Calgary community engagement initiatives, as well as assess the disparity between the students’ and the university’s understanding of community engagement. With further understanding of the students’ knowledge of UCalgary’s community engagement initiatives, we anticipate that this research will serve as a gateway to explore communicative methods to better convey the university’s priorities to the students. The results will derive student identified priorities which will be instrumental in building a campus-wide community engagement initiative which is student-informed. We intend for this study to supplement additional research in the area of community engagement.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".