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Record W2031772921 · doi:10.1007/s11606-010-1550-3

Sounds of Haiti

2010· article· en· W2031772921 on OpenAlexaboutno aff
Sriram Shamasunder

Bibliographic record

VenueJournal of General Internal Medicine · 2010
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGeneral surgeryMedical emergencySurgery

Abstract

fetched live from OpenAlex

There is always humming from somewhere. It is usually low and musical as patients try to distract themselves from phantom limb pain that is not at all phantom. It is 13 days after the earthquake. I am coordinating a 12-member team at St. Marc’s hospital, a government facility on the west coast of Haiti. For the 2 years prior to the quake, Partners in Health has supported the site with materials and salary. An orthopedic surgeon, a plastic surgeon, an anesthesiologist, an emergency room physician and five nurses are with me from the Brigham and Women’s Hospital in Boston. There is a friendly Haitian pastor who walks daily into the medical ward. He raises his hands and prays loudly in Creole for roughly 4 minutes. I only understand the “Amen!” at the end. He always shakes my hand before he leaves the room. Many people here think the quake is divine intervention for lives lived wrong. The first few days lacked nuance. Limbs required amputation and open fractures, fixation. Patients were prioritized based on their likelihood of death now, or later. There are roosters and dogs at five in the morning. There is a generator running outside. They wake us up. There is the beeping of one of our only portable oxygen monitors as a baby’s saturation starts to dwindle. We have lost three babies in 3 days from dehydration, cerebral malaria and bowel obstruction. None of these is strictly earthquake related. Now we reshuffle and reprioritize the massive case load of wound debridement, skin grafts and fractures, weighing them against other crises that enter continuously through the door. After seeing a third child this week die of pneumonia, or dehydration or cerebral malaria, we clearly understand that this country existed in a state of emergency long before the earthquake: an emergency without enough witnesses. The earthquake exacerbated an existing bleed. The country is now hemorrhaging. There is the rapid, open mouth pant of asthmatic children, of anxious and anemic mothers, of old men in heart failure. Over the last few days, challenges have mounted. We balance tending the flood of patients created directly by the earthquake and treating the ongoing everyday trauma, heart failure, diabetic coma, malaria and severe dehydration of a destitute population. Each day, we are challenged by running one hospital—not two parallel American and Haitian hospitals. Our goal is one Haitian hospital with lasting effects benefitting the population long after we leave. There is the click-clank of walkers as so many amputees start to ambulate. They break into a grimace, smile, laugh as so many get up for the first time since the earthquake. French Creole music blares from the headphones of the 15-year-old amputee as I come to round on her in the late afternoon. How the hell are the Haitian people so tough? How did they absorb the brutal shaking of the earth into their bones, and still endure? The last few days reveal what they have always had to deal with—death from dumb, treatable diseases. Haitians have always known their lives were not entirely or even mostly in their hands. The earthquake was more proof, brutal and all at once. In the fog of all that is chaotic and difficult, I witness an awe-inspiring collaboration among so many people that imbues in me a certain deep faith in humanity. There is the general absence of any sound of any violence. Necrotizing fasciitis liquefies the muscles of one of our sickest patients. He sinks into sepsis, barely arousable, but his pulse remains strong. We quickly run out of options in this hospital. Through a friend of a friend, we contact the Canadian Embassy. The Canadians immediately send a helicopter, which lands on a nearby soccer field. There is the barely audible guttural grunt of acceptance from his family member, who agrees to transport to Canada or the USNS Comfort for a higher level of care. Families are unable to accompany patients during transport for reasons beyond my control. This is the height of vulnerability, of powerlessness. For the hope of healing, Haitians routinely give up their own into the hands of an unknown skilled foreigner who takes them somewhere other than Haiti. We make our way to the secure field. As we load our patient onto the helicopter, Haitians hang off the fence in all directions to catch a glimpse—hundreds of them. We get airborne and make our way 40 minutes in the chopper to the USNS Comfort, a military ship that has the capabilities of a full-fledged fancy US hospital, including operating rooms. An entire massive US military ship dedicated to Haitian patient care. Not an occupation, not men with guns who parade around a foreign land like they own it. The ship contains a solid trauma bay with some of the best American doctors. As we leave our patient and rise into the air, I think that maybe the United States can rewrite its sordid history on this island. Maybe the USNS Comfort and the dedicated Americans I have met over the last 2 weeks represent that shift. I am on the ground. I am not sure what the 10,000 foot plan looks like. Development and implementation of a successful plan will require direction, prioritization and commitment on the part of both Haitian and international leaders. Meanwhile, the Haitians are gritting their teeth and starting to walk on their one foot. Amazing medical teams from around the world are ready to accompany them, hobbling slowly and surely together to some better horizon.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.141
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1410.027

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 head0.055
GPT teacher head0.458
Teacher spread0.403 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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