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Record W7007849152

All Party Green Agenda Newfoundland & Labrador 2011 Provincial Election

2011· report· en· W7007849152 on OpenAlexaboutno aff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2011
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityNatural resourceGovernment (linguistics)RevenuePoliticsLivelihoodSustainable developmentSustainabilityEnvironmental governance
DOInot available

Abstract

fetched live from OpenAlex

Newfoundland and Labrador possesses a wealth of natural and environmental resources. This includes important wildlife habitat, forest, freshwater and marine ecosystems. With such wealth comes a duty to protect and enhance the natural environment. The 2011 provincial election is a watershed election for the province. After several years of prosperity which has seen significant revenues from non-renewable offshore resources invested to modernize public infrastructure such as hospitals, roads and schools among other things, the opportunity exists for the next government to chart an environmentally friendly and sustainable future for all Newfoundlanders and Labradorians. This bold innovative environmental future is to focus on: • embracing alternative energy resources; • protecting our peatlands resources; • investing in leading edge waste management practices; • reducing the environmental impacts of the oil industry; • moving to less carbon intensive practices; • repositioning the forestry sector to recognize its diversity and to ensure its environmental sustainability; and, • working to create a food production system that is less dependent on imports. It is to these issues that this environmental brief seeks commitment from all political parties in the 2011 provincial election.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.400
Threshold uncertainty score0.805

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.2140.065

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 head0.089
GPT teacher head0.299
Teacher spread0.211 · 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
Published2011
Admission routes1
Has abstractyes

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