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Record W2016143602 · doi:10.1017/s1049023x12001690

Academic Affiliated Training Centers in Humanitarian Health, Part I: Program Characteristics and Professionalization Preferences of Centers in North America

2013· article· en· W2016143602 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePrehospital and Disaster Medicine · 2013
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsProfessionalizationHumanitarian aidHealth carePolitical sciencePublic relationsMedical educationMedicineLaw

Abstract

fetched live from OpenAlex

Abstract The collaborative London based non-governmental organization network ELRHA (Enhancing Learning and Research for Humanitarian Assistance) supports partnerships between higher education institutions and humanitarian organizations worldwide with the objective to enhance the professionalization of the humanitarian sector. While coordination and control of the humanitarian sector has plagued the response to every major crisis, concerns highlighted by the 2010 Haitian earthquake response further catalyzed and accelerated the need to ensure competency-based professionalization of the humanitarian health care work force. The Harvard Humanitarian Initiative sponsored an independent survey of established academically affiliated training centers in North America that train humanitarian health care workers to determine their individual training center characteristics and preferences in the potential professionalization process. The survey revealed that a common thread of profession-specific skills and core humanitarian competencies were being offered in both residential and online programs with additional programs offering opportunities for field simulation experiences and more advanced degree programs. This study supports the potential for the development of like-minded academic affiliated and competency-based humanitarian health programs to organize themselves under ELRHA's regional “consultation hubs” worldwide that can assist and advocate for improved education and training opportunities in less served developing countries. Burkle Jr FM, Walls AE , Heck JP , Sorensen BS , Cranmer HH , Johnson K , Levine AC , Kayden S , Cahill B , VanRooyen MJ . Academic affiliated training centers in humanitarian health, Part 1: program characteristics and professionalization preference of centers in North America . Prehosp Disaster Med . 2013 : 28 ( 2 ): 1 - 8 .

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)0.000
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 score0.210
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

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

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 head0.069
GPT teacher head0.374
Teacher spread0.305 · 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