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Record W3085108930 · doi:10.1186/s40545-020-00256-w

The Urgent Need for Transparent and Accountable Procurement of Medicine and Medical Supplies in Times of COVID-19 Pandemic

2020· article· en· W3085108930 on OpenAlex
Jillian Clare Köhler, Tom Wright

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Pharmaceutical Policy and Practice · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Toronto
FundersCenter for Substance Abuse PreventionLeslie Dan Faculty of Pharmacy, University of TorontoUniversity of Toronto
KeywordsTransparency (behavior)ProcurementPandemicLanguage changeBusinessAccountabilityCoronavirus disease 2019 (COVID-19)Public healthQuality (philosophy)Public relationsPolitical scienceMedicineMarketingInfectious disease (medical specialty)LawNursing

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has unleashed unprecedented and complex public policy issues. One that has emerged as a challenge for many countries globally is how to ensure the efficient and effective procurement of quality medical supplies. Existing corruption pressures on procurement-everything from undue influence to the outright bribery of public officials-has been amplified by the pandemic, and thus demands commensurate policy responses. We argue that transparency and accountability in procurement are essential to preventing the corruption risks that threaten the health and well-being of populations.

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)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.878
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
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 head0.207
GPT teacher head0.505
Teacher spread0.298 · 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