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GOING GLOBAL

2017· article· en· W2773935888 on OpenAlexaboutno aff
Kate Banks

Bibliographic record

VenueEmergency Medicine News · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careFamily medicineInterpreterMedicineGovernment (linguistics)Work (physics)GeographyNursingPolitical science

Abstract

fetched live from OpenAlex

FigureThe Himalayan Health Exchange (HHE) is an organization that assembles volunteers and health care providers from all over the world to deliver care in underserved areas in northern India. I had the amazing opportunity in my second year of residency to spend a month delivering medical care with HHE in the beautiful inner Himalayan mountains. The month was full of exploring, trekking, camping, learning, doctoring, and personal and professional growth. The clinics were scattered throughout different areas in the state of Himachal Pradesh. Our convoy of interpreters, cooks, volunteers, and health care professionals made camp in remote villages or in the mountains near small towns. Clinics were generally held in the areas close to our campsite. HHE visits these sites several times a year, so the local residents are familiar with their group and there is a small degree of continuity. Patients came from all over to see the physicians at our clinics. One patient, who was in the second trimester of pregnancy, walked more than 18 kilometers through the mountainous terrain to see a doctor. We also held clinics at schools and orphanages. After clinic, we had educational sessions about hygiene and dental care. Luckily for our patients, physicians and government hospitals will see them for free or at reduced rates. Access to health care, however, can be quite far geographically, and may require a one- or two-day trip. Most people cannot afford the transportation fare or missing several days of farming or work to see a physician, unless it is very serious. Most patients had benign complaints such as poor vision, arthritis, or gastritis. These people were so thankful when we provided them with simple remedies such as reading glasses, ibuprofen, or Zantac. It was refreshing to see how grateful they were for medications that we have readily available in the United States and take for granted. The simplicity of medicine in India was sometimes invigorating, but I found myself yearning for modern technology several times. I had a teenager with mastoiditis who could not go to a hospital for several weeks, so I placed him on an oral third-generation cephalosporin. I still agonize over that case, and wish I'd done a CT scan to determine if the patient needed surgical debridement or if antibiotics were sufficient to treat his condition. Another patient presented with a benign complaint, but had a pulsatile abdominal mass on exam. I wanted to perform a bedside ultrasound so badly to confirm my suspicion of an abdominal aortic aneurysm, but that was impossible. We stressed the importance of going to a hospital for evaluation of this potential ticking time bomb, but I don't know if she was able to make it. Besides treating Indian and Himalayan patients, our trip also provided care to Tibetan refugees. Many Tibetan refugees followed the Dalai Lama to northern India when he was exiled. Because of this, a large Tibetan and Buddhist population mixed with the traditional Indian Hindu population in Himachal Pradesh. This made for a very interesting and varied cultural experience. We held clinics at Buddhist nunneries, monasteries, and schools where Tibetan children study while preserving their language and culture. Our group consisted of undergraduate students, medical students, residents, and attending physicians from all over the world. We had people from the United States, England, Australia, Italy, Canada, and India. It was so interesting to learn the way medical education and health care work in each of these diverse countries. We would often sit around the campfire and talk about our respective cultures. I learned a lot about these different cultures' philosophies, food, language, and so much more. This trip was truly once in a lifetime. Looking back on my residency, I will always remember my month-long journey trekking through the Himalayas and providing care to such wonderful patients. I am blessed that the Himalayan Health Exchange and my residency program allowed me to have such a gratifying and life-changing experience.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.748
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.7480.654

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.

Opus teacher head0.064
GPT teacher head0.409
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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