Bibliographic record
Abstract
“Doula needed for primip in Room 6. Spanish speaker. Eighteen years old. Alone. Wants to go natural. Time: 11:30 pm.” My phone lights up with this message just after I close my anatomy textbook and get in bed. I pause with my hand on my bedside lamp, listening to the rain thump angrily against my bedroom window. For a moment, I consider staying under the warmth of the covers, but then I pick up my phone and dial the number for Labor and Delivery. “Hi, I’m one of the volunteer doulas,” I say. “Just wanted to let you know I’m on my way.” The word doula is Greek—it translates directly to women’s servant. A doula’s role is to provide continuous physical, emotional, and informational support to women during childbirth. As a member of the hospital’s volunteer doula program, I work alongside a trained group of dedicated volunteers. While some are medical students like me, others are studying nursing or public health and still others have no medical background whatsoever. Whenever there is a need for a doula as decided by the labor and delivery nurses, we all receive a message, and one of us reports to the hospital—even when, as with tonight, it means exchanging pajamas for a raincoat and scrubs. By midnight, I am walking through the door of Room 6. I see a young woman sitting on the edge of the bed, her cheeks flushed. Her dark hair is pulled back into a messy bun, with thin strands sticking to her forehead. My Spanish is far from perfect, but I do my best to introduce myself to the patient and explain to her why I am there. “I will be here to help you,” I tell her, “until the baby is born.” At this, she raises her eyebrows, confused at such a promise. “No matter how long it takes?” she asks. I nod. “No matter how long it takes.” She smiles, but her eyes remain anxious and wide. As the night goes on, her contractions become more and more intense. I go through my toolbox of doula techniques. I work with her through breathing and position changes. She labors in the bed, on a birth ball, and in the tub. I cover her forehead in cold compresses and wrap her body in warm blankets. I apply pressure to her hips and back during contractions, and provide therapeutic massage to help her stay calm. By 8 am, her cervix is seven centimeters dilated and her strength is waning. She is lying on her side, and I am standing behind her. I watch the monitor trace her contractions on the screen—each time the line begins to peak, I apply pressure to her hips and back and coach her through the pain until it comes back down. Suddenly noticing the ache in my legs, I pull up a stool beside the bed and sit. Between the next two contractions, staring at the screen, I realize that my eyes are closing. I tap my feet on the ground, trying to stay awake. What would the nurse think if she came in and saw me falling asleep on the job? Or, worse, the OB/GYN who would be my attending next year? After all, snoozing beside a patient is not exactly in my job description! Looking at the patient, I see that she has closed her eyes, too. “That’s good,” I encourage her. “Try to sleep as much as you can. It will give you energy when it’s time to push.”The Gold–Hope Tang, MD 2016 Humanism in Medicine Essay Contest Each year, the Arnold P. Gold Foundation holds an essay contest to encourage medical students to reflect on their experiences and engage in narrative writing. The contest, launched in 1999 and open to any student enrolled in an accredited U.S./Canadian medical school, asks students to respond to a specific prompt in a 1,000-word essay. The 2016 prompt was “Sometimes the most important thing in a whole day is the rest we take between two deep breaths.”—Etty Hilliesum. Talk about a time when you or a team member had to step back and practice self-care while helping a patient. More than 160 essays were submitted and reviewed by a distinguished panel of judges ranging from esteemed medical professionals to notable authors. The top three essays were selected along with 10 honorable mentions. Winning essays were published on the Arnold P. Gold Foundation Web site (www.humanism-in-medicine.org) and will be published in consecutive fall issues of Academic Medicine. The contest is named for Hope Babette Tang-Goodwin, MD, who was an assistant professor of pediatrics. Her approach to medicine combined a boundless enthusiasm for her work, intellectual rigor, and deep compassion for her patients. She was an exemplar of humanism in medicine. The Arnold P. Gold Foundation, founded in 1988, is dedicated to creating the Gold Standard in health care—compassionate, collaborative, and scientifically excellent care—to support clinicians throughout their careers, so the humanistic passion that motivates them at the beginning of their education is sustained throughout their practice.The next time I find myself nodding off, rather than silently scolding myself, I decide to take my own advice. I put my hand in hers, let my guard down, and rest. From that moment onward, we fall into a rhythm. I do not even need to peek at the screen to know she is having a contraction—I simply feel her hand tighten in mine, stirring me from sleep. During contractions, I work with her through the pain, just as I had been doing. And between contractions, hand-in-hand, we sleep. My role as a doula requires me to throw my head and my heart into my job quite fully, and as a first-year medical student, I aspire to a career as a physician that involves a similar degree of mental and emotional investment. There is something to be said for that level of focus, that level of concentration. But at the same time, I have come to realize the danger of becoming so focused on the needs of a patient that I forget my own. I know now that in doing so, I may do both my patient and myself a disservice. In this case, recognizing my own need for rest helped me form a closer bond with my patient. Despite our different backgrounds and the language barrier, after I let my guard down and we fell into a pattern of sleeping and waking together, we were remarkably in sync. In addition to being patient and provider, we began to feel like a team tackling a difficult experience side-by-side. There was no superhero in that hospital room—just two humans working together. Additionally, just as my patient was more ready when the time came to push because she had slept, I felt refreshed and energized, too. At the final stretch when she needed me most, and then when her baby boy’s head appeared and we heard his shrill cry, I was both physically and mentally present because earlier, I had recognized my own need for rest. The words “self-care” are not often praised in medical school, and they do not tend to make their way into job descriptions. But that night I learned that sometimes, a little rest can go a long way, both for my patients and for myself.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.040 | 0.009 |
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".