Bibliographic record
Abstract
‘Push hard, hard, hard’! In the midst of the delivery room, the family medicine doctor urged the labouring mother. It was a stark contrast to just hours earlier when the same doctor had echoed those words while curling at the local club. The connection between these seemingly unrelated events began earlier that evening when, on my first clinical placement in rural Southwestern ON, the doctor invited me to join a curling session. I had just arrived the day before, and curling was evidently a community staple. Intrigued, I accepted the invitation. As we prepared a patient for induction, the doctor explained the local enthusiasm for curling. My response revealed my limited experience, having curled only once in gym class. Undeterred, the doctor encouraged me to join that evening, setting the stage for an unexpected blend of medical observations and community integration. ‘Hurry hard, hard, hard’! My preceptor shouted down the ice as I scooted with my broom awkwardly towards the button, fighting to keep my balance. After a long day in the clinic, this break from the hospital was exactly what I needed. Amidst the excitement of the curling game, the doctor asked if I wanted to be notified when the labouring mother was ready to push. Eager for the experience, I enthusiastically agreed. As a 2nd-year medical student, with limited hospital exposure, I was excited to witness my first birth. ‘Even if it is at 2 am?’ She clarified. ‘Absolutely’. In the backdrop of my medical school studies, I had explored the decline of family practice obstetrics in rural Ontario. Reasons such as fear of litigation and challenging call schedules had contributed to the emergence of ‘maternal care deserts’ across the province over the past 20 years.1 Ironically, before this placement, I had dismissed obstetrics as a potential career path due to similar concerns. I returned to the hospital that night at 11 pm, hardly past my bedtime and I observed the intensity of labour. The doctor and nurses guided the mother through contractions, and I played a supporting role, handing supplies and offering encouragement. The wave of emotions in the room once Mom gave the final push, and a gush of fluid arrived with a screaming babe, overcame me. I was in awe of Mom’s strength and the doctors calm and collected approach to the delivery. ‘Did you see that, Dad? It’s a boy’! The Doc exclaimed, as she quickly inspected the baby and placed him on Mom’s chest. The parents had not been informed of the sex earlier in the pregnancy, so they were just as surprised as I was to welcome their son into the world. ‘Welcome, Jack’, our patient exclaimed exhausted after the past 12 h of labour. ‘Would you like to cut the cord, Dad?’ The doctor offered, he shook his head vigorously, after which the physician offered this experience up to me, which I eagerly accepted. Once Mom and babe were settled, I returned home after a long day. I reflected about the day’s events, with a new appreciation for the family medicine generalist as an avenue for obstetrical care in rural communities.2 I went to bed that night with my previous preconceptions about rural obstetrical care obliterated, an excitement about rural obstetrical care that I am excited to bring into my future career as a rural family physician and a new appreciation of the challenges and joys of curling. Financial support and sponsorship: Nil. Conflicts of interest: There are no conflicts of interest.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".