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Record W7053271668

Workshop: Canadian-Nigerian Human Rights Cooperation (1999-2011) (April 2014)

2014· article· en· W7053271668 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicChemical and Physical Properties of Materials
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipHuman rightsJoint (building)Focus (optics)Field (mathematics)Work (physics)
DOInot available

Abstract

fetched live from OpenAlex

hursday, May 8 – Saturday, May 10, 2014 Background and Conference Theme\nThe Osgoode-Nathanson/NIALS/CENSOJ Partnership Development will be holding a workshop on May 8-10, 2014 at Osgoode Hall Law School. The workshop, hosted by the Nathanson Centre, will focus on Canadian-Nigerian human rights cooperation between 1999 and 2011.\nLed by Professor Obiora Okafor (Osgoode/Nathanson), Professor Dakas C.J. Dakas (NIALS) and Mr. Eze Onyekpere (CENSOJ), the workshop is part of a four-year collaborative research and dissemination project funded by the Social Sciences and Humanities Research Council of Canada. The purpose of this workshop is to engage in joint academic debate and knowledge mobilization about the nature, attainments, problems and prospects of human rights cooperation between Canada and Nigeria.\nDraft analytical papers reporting the preliminary results of the field research conducted so far by our joint research team in Canada and Nigeria will form the starting point of the discussions at the workshop.\nIf you are interested in participating in the workshop, or for further information, please contact conference coordinator Terrine Friday at terrinefriday@osgoode.yorku.ca. Second Osgoode/NIALS/CENSOJ Partnership Development Program Workshop\nCanadian-Nigerian Human Rights Engagements: A Critical AssessmentJune 1-2, 2015Venue: The National Judicial Institute, Airport Road, Abuja\nConference Programme\nSee attached file.\nConference Papers\nSee additional files.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0250.010

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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
Published2014
Admission routes1
Has abstractyes

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