MétaCan
Menu
Back to cohort
Record W7033344474

Public health program evaluation best practices within the Canadian federal government [research project] / by Agate Stankiewicz.

2017· other· en· W7033344474 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typeother
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionHyporeflexiaTSG101DiafiltrationGestational periodPretext
DOInot available

Abstract

fetched live from OpenAlex

Program evaluation findings are reported in evaluation reports as part of Treasury Board
\nof Canada Secretariat (TBS) funding requirements and are key information used to ensure
\naccountability for planned results. This project critically appraises the Public Health
\nAgency of Canada?s (PHAC) eight program evaluation reports for their strengths and
\nweaknesses - program evaluation planning, design and implementation, data collection
\nand analysis, and reporting - for informing public health practice. First, these reports are
\nappraised using a modified version of the review template obtained from the ?Review of
\nthe Quality of Evaluations Across Departments and Agencies?, developed by the TBS.
\nThese findings are then reviewed in light of public health program evaluation guidelines
\nfor compliance with the standards of public health evidence, as well as the current TBS
\nEvaluation Policy (2001) for compliance with the standards of performance reporting.
\nThe project concludes with recommendations to advance public health program
\nevaluation planning, design and implementation, data collection and analysis, and
\nreporting in the joint context of public health practice and the Canadian federal
\ngovernment accountability for performance.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0000.001
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 head0.293
GPT teacher head0.396
Teacher spread0.103 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueKnowledge Commons (Lakehead University)Same topicUser Authentication and Security SystemsFrench-language works237,207