Insight on Food : An analysis of the nutritional knowledge of first year students living in Totem Park Residence
Bibliographic record
Abstract
Many undergraduate students lack the ability to appropriately assess, prioritize, and improve their level of nutrition according to research on Canadian campuses (Boland et al. 2014). Undergraduate admission at UBC has increased significantly in recent years. Since many of these students are away from home for the first time, support to encourage judicious food choices may be in order. Though many other Canadian universities have conducted studies assessing nutritional knowledge in undergraduates with relevance to Canadian Food Guide groups and individual nutrients, no existing literature was found to compare levels of knowledge regarding multiple nutrients within a single study. In addition, no known studies relating to nutrition literacy have been conducted at any of UBC’s residences. The main goal of this study was to highlight the nutritional knowledge gap of first-year students in residence nearing the completion of their academic year to help guide future nutritional education initiatives. Specific objectives include elucidating student’s level of familiarity with individual nutrients (vitamin D, calcium, omega-3 fatty acids, sodium, fibre, and iron) and the sources of these nutrients in the dining hall. The specific nutrients were chosen in collaboration with Ms. Nicole Fetterly, Registered Dietician and Manager of Nutrition & Wellness at UBC Student Housing and Hospitality Services. The data provides a snapshot of the nutritional knowledge of UBC’s first-year student in residence. The survey took place at Totem Park Residence dining hall with 125 first year students participating in March 2016. The survey was designed to address confidence in nutritional knowledge and, for students who felt somewhat or very confident, test actual knowledge on sources of specific nutrients. There was a clear nutritional knowledge deficit specifically regarding calcium, iron, protein and vitamin D. The general trends observed were summarized in four categories: nutrients with high confidence and knowledge levels (fibre and sodium); high confidence and low knowledge levels (protein); nutrients with low confidence and high knowledge levels (omega-3 fatty acids); and nutrients with low confidence and knowledge levels (calcium, iron and vitamin D). Our findings demonstrate the importance of establishing measures to improve nutrition knowledge of first-year students at UBC. The results of this survey can be used to help guide the establishment of future programs and services, directly contributing to the health and well-being of the undergraduate population, during and beyond their university careers. We recommend public display such as signage and posters, peer health educators and cooking demonstrations. Future research on the impact of cultural background on food choices and understanding of nutrient functions is also strongly recommended. 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".