Maternal Impressions of the New 2019 Canadian Food Guide
Bibliographic record
Abstract
Background: Canada’s new food guide was released on January 2019 followingits predecessor Eating Well with Canada’s Food Guide released in 2007. Major changes in the new food guide included a partitioned plate of realfoods, messages around healthy eating being more than the foods you eat, and no feature of the milk and alternatives group. There were also no recommended servings for age groups or developmental stages including pregnant women. Objective: The purpose of this qualitative study was to explore the perceptions of pregnant Canadian women toward the new Canada food guide.Methods: Eight pregnant women over the age of eighteen were recruited from facilities that offered prenatal fitness. Interviews included documenting impressions of the Canada food guide, dietary choices during pregnancy and planned dietary changes. The interviews were digitally recorded, and transcribed verbatim. Braun and Clarke thematic analysis was used to analyze the data.Results: All the participants were familiar with Canada food guides and all but three were aware of the newest version. Participants commented that the new food guide was appealing and healthy. Most participants had already madechanges to their daily diet that coincidentally corresponded to the new food guide. Many also followed the messages in the new food guide but reported that pregnancy was the main influence for food changes. Participants included more fruits and vegetables, and less meat than when they were not pregnant.The internet, family, physicians and previous knowledge were also used to inform food choices. Much of this information was however reported as too little and contradictory. Participants wanted information more specific to pregnant women which was not included in the new food guide.Conclusions: Canada’s new food guide reinforced actions that women were already taking to improve their diet during pregnancy. The new food guide offers broad recommendations for Canadians to follow but pregnant women prefer a guide that is specific with clear recommendations for pregnant women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".