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Record W6997320926

Weathering the Political and EnvironmentalClimate of the Kyoto Protocol

2004· report· en· W6997320926 on OpenAlexaboutno aff

Bibliographic record

VenueoURspace (University of Regina) · 2004
Typereport
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsKyoto ProtocolGreenhouse gasTreatyPrime ministerMontreal ProtocolLimitingPoliticsHouse of CommonsClimate change
DOInot available

Abstract

fetched live from OpenAlex

When Canada’s Minister of the Environment, David Anderson, notified the United Nations (UN) on 17 December 2002 that Canada would ratify the UN Framework Agreement on Climate Change, known best as the Kyoto Protocol, Canada joined nearly 100 countries to do so. Together, these countries represented about 40 per cent of the 1990 emissions, still some distance from the 55 per cent threshold necessary for the UN Agreement to come into effect. A day earlier, then Prime Minister Jean Chretien had signed the 1997 treaty limiting greenhouse gas emissions at a ceremony in Ottawa after the House of Commons had approved the treaty. Because the United States, which is responsible for more than 36 per cent of all emissions, had rejected the treaty, there was great hope that Russia would soon ratify the protocol. Once Russia became a signatory to the agreement, it and all other signatories would have committed themselves to reducing greenhouse gas emissions to six per cent below 1990 rates by 2012. In Canada, that necessitated a reduction of 20 to 30 per cent from current levels. However, Russia, like the United States and Australia, has not yet ratified the Kyoto Protocol and, without Russia, which accounts for 17.4 per cent of emissions, the Protocol may be in serious trouble.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.197
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.035
GPT teacher head0.301
Teacher spread0.266 · 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 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
Published2004
Admission routes1
Has abstractyes

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