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Record W2141350385 · doi:10.1017/dmp.2013.10

Competency-Based Standardized Training for Humanitarian Providers: Making Humanitarian Assistance a Professional Discipline

2013· article· en· W2141350385 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

VenueDisaster Medicine and Public Health Preparedness · 2013
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsProfessionalizationCore competencyAccountabilityTraining (meteorology)Medical educationHumanitarian aidPsychologyPublic relationsNursingBusinessMedicinePolitical scienceMarketing

Abstract

fetched live from OpenAlex

The number of people employed in international humanitarian care is growing at a yearly rate of 6%. The demand for better coordination, accountability, and training has led to a need for standardized humanitarian training programs for providers. Training should be based on comprehensive core competencies that providers must demonstrate in addition to their skill-specific competencies. This report explores the competencies specific to humanitarian training that are practice- and application-oriented, teachable, and measurable. Competency-based, standardized programs will be used to select humanitarian workers deployed in future crises and to guide the professionalization of this discipline.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
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 head0.188
GPT teacher head0.456
Teacher spread0.268 · 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