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Record W6888567850 · doi:10.20381/ruor-22987

Lessons from the Interagency Emergency Health Kit for access to essential medicines in Canada

2019· other· en· W6888567850 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEssential medicinesAccess to medicinesRefugeeHealth careGlobal healthPosition paperPosition (finance)

Abstract

fetched live from OpenAlex

Abstract Despite Canada’s efforts to position itself as a global health leader, important medicines, including multiple drugs found on the WHO Model List of Essential Medicines, are not available domestically. Of the fourteen medicines found in the Interagency Emergency Health Kit, the most basic distillation of the global health toolkit designed for responding to acute humanitarian crises, only ten are currently sold in Canada; alternative treatments that are available may not be as effective or affordable. Their absence highlights broader issues with Canada’s market-driven system of access to medicines, with implications for the care of refugees and other populations, while serving as a reminder of the importance of ensuring access to essential medicines in all settings.

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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.118
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0180.006
Scholarly communication0.0120.004
Open science0.0040.005
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0340.002

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 head0.019
GPT teacher head0.259
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2019
Admission routes1
Has abstractyes

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