Bibliographic record
Abstract
No accessJournal of Human SecurityEditorial01 January 2011Guest Editorial Authors: Rose A Dyson Authors: Rose A Dyson Chair, Media Working Group, Science for Peace, and Director, Communications for the Canadian Peace Research Association, email: [email protected] Google Scholar More articles by this author SectionsAboutPDF/EPUBExport CitationsAdd to FavouriteAdd to FavouriteCreate a New ListNameCancelCreate ToolsTrack CitationsCreate Clip ShareFacebookTwitterLinkedInEmail Next article RelatedDetails View PUBLICATION DETAILSDate of Publication:January 2011Journal:Journal of Human SecurityISSN:1835-3800Volume:7Issue:1Page Range:1-5First Page:1Last Page:5Source:Journal of Human Security, Vol. 7, No. 1, 2011: 1-5Date Last Modified:05 September 2018 12:24Date Last Revised:06 October 2012 Original DOI: 10.3316/JHS0701001SubjectViolenceMass mediaMass media policyCommunication--Technological innovationsHuman securityMass media--Social aspectsInternet--Psychological aspects METRICS Downloaded 0 times Copyright© Human Security Institute, 2011Download PDFLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.331 | 0.192 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".