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Record W2519008100 · doi:10.1186/s40064-016-3046-z

Financial contributions to global surgery: an analysis of 160 international charitable organizations

2016· article· en· W2519008100 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSpringerPlus · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueHealth careLiberian dollarFinanceSpecialtyCurrencyBusinessMedicineEconomicsFamily medicineEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: The non-profit and volunteer sector has made notable contributions to delivering surgical services in low-and middle-income countries (LMICs). As an estimated 55 % of surgical care delivered in some LMICs is via charitable organizations; the financial contributions of this sector provides valuable insight into understanding financing priorities in global surgery. METHODS: Databases of registered charitable organizations in five high-income nations (United States, United Kingdom, Canada, Australia, and New Zealand) were searched to identify organizations committed exclusively to surgery in LMICs and their financial data. For each organization, we categorized the surgical specialty and calculated revenues and expenditures. All foreign currency was converted to U.S. dollars based on historical yearly average conversion rates. All dollars were adjusted for inflation by converting to 2014 U.S. dollars. RESULTS: One hundred sixty organizations representing 15 specialties were identified. Adjusting for inflation, in 2014 U.S. dollars (US$), total aggregated revenue over the years 2008-2013 was $3·4 billion and total aggregated expenses were $3·1 billion. Twenty-eight ophthalmology organizations accounted for 45 % of revenue and 49 % of expenses. Fifteen cleft lip/palate organizations totaled 26 % of both revenue and expenses. The remaining 117 organizations, representing a variety of specialties, accounted for 29 % of revenue and 25 % of expenses. In comparison, from 2008 to 2013, charitable organizations provided nearly $27 billion for global health, meaning an estimated 11.5 % went towards surgery. CONCLUSION: Charitable organizations that exclusively provide surgery in LMICs primarily focus on elective surgeries, which cover many subspecialties, and often fill deep gaps in care. The largest funding flows are directed at ophthalmology, followed by cleft lip and palate surgery. Despite the number of contributing organizations, there is a clear need for improvement and increased transparency in tracking of funds to global surgery via charitable organizations.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.318
Teacher spread0.307 · 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