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Record W2907906725 · doi:10.4324/9781351148283-17

Civil Society Engagement: A Case Study of the 2002 G8 Environment Ministers Meeting

2017· book-chapter· en· W2907906725 on OpenAlexaboutno aff
Sheila Risbud

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicInternational Environmental Law and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceCivil societyAeronauticsPublic administrationEngineeringLawPolitics

Abstract

fetched live from OpenAlex

This chapter examines the Canadian-hosted G8 environment ministers meeting held in Banff, Alberta, on 12-14 April 2002 as an example of civil society engagement in the G8 process. It highlights both the successes achieved and the improvements needed in the Canadian government&s;s outreach and engagement programme. The chapter addresses lessons learned from this event and how these lessons can be applied to future ministerial meetings and summits. The town hall session was followed by a series of one-on-one meetings between senior officials and individuals or groups who requested more information or who wanted to provide input into the process. These individuals and groups included local environmental groups, businesses, town leaders, and the interested average individuals on the street. The youth drafted a declaration and presented it at the minister&s;s round table meeting. The forum gave youth a new and positive relationship with the Royal Canadian Mounted Police and Environment Canada.

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)0.005
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0430.010
Scholarly communication0.0110.005
Open science0.0030.008
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0130.002

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 head0.027
GPT teacher head0.235
Teacher spread0.208 · 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
Published2017
Admission routes1
Has abstractyes

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