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Record W2002691556 · doi:10.5210/ojphi.v5i1.4453

Advancing Surveillance Outside the USA: The Canadian Policy, Practice, and Research Context

2013· article· en· W2002691556 on OpenAlexaffabout
Effie Gournis, David L. Buckeridge

Bibliographic record

VenueOnline Journal of Public Health Informatics · 2013
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMcGill UniversityUniversity of TorontoToronto Public Health
Fundersnot available
KeywordsContext (archaeology)Political sciencePublic relationsWork (physics)PoliticsFocus (optics)Public administrationData scienceComputer scienceLawGeographyEngineering

Abstract

fetched live from OpenAlex

In the spirit of strengthening the International presence of ISDS, this round table will explore how ISDS can support surveillance practitioners and researchers in Canada and similar countries as they work to advance surveillance in their own political and practice contexts. Results from a survey circulated to Canadian ISDS members and affiliates will guide this discussion, which will focus on delineating specific needs, actions, and ways ISDS might be able to support Canadian members.

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)0.042
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.750
Threshold uncertainty score0.870

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.068
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0350.018
Scholarly communication0.0210.006
Open science0.0050.012
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0080.000

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 head0.148
GPT teacher head0.466
Teacher spread0.318 · 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 designQualitative
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
Published2013
Admission routes2
Has abstractyes

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