Creating a Lactation-Friendly Learning Environment for Medical Students and Residents: A Northern Canadian Perspective
Bibliographic record
Abstract
Background: Lactation is a normal postpartum physiological process that can continue in excess of 3 years and is often the sole nutritional source for infants in the first 6 months of life. Breastfeeding not only provides infant nutrition, but also facilitates maternal–infantile bonding. Lactating mothers separated from their children face multiple challenges in finding and accessing appropriate spaces and time for milk expression. Maternal employment is a great barrier to breastfeeding and accordingly has led to multiple advancements in the area of breastfeeding policy. One example of a policy is the Baby-Friendly Initiative. This initiative focused on breastfeeding promotion, support, and protection. However, the impact of such campaigns on lactating medical students and residents is thought to be low. Furthermore, breastfeeding rates differ vastly according to geographic locations in North America. Trends indicate decreased rates of breastfeeding in northern rural areas in comparison with southern urban counterparts. This highlights the need for increased protection, support, and creation of safe-lactation spaces for all working mothers including medical students and residents, and especially those in rural areas. Goals: To review challenges of breastfeeding as a medical trainee and delineate the creation of a lactation policy for medical learners and residents. Methodology: We conducted a literature review of breastfeeding policy and experiences of breastfeeding while in the learning environment. Results: Challenges of breastfeeding in medical school and residency include the complex, high-paced medical working environment where taking breaks or time off is often difficult. Few medical schools across North America have any breastfeeding policy. Conclusion: The Northern Ontario School of Medicine's lactation policy serves as a possible solution to the barriers medical students and residents face when breastfeeding in the academic environment. This policy creates lactation-friendly medical learning spaces through the entitlement of dedicated space and time for milk expression.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.024 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".