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Record W7100382156

Spent Lead Shot and the Environment: A Topical Environmental Education Issue for Schoolchildren, Especially Rural Canadians and

2016· article· en· W7100382156 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsShot (pellet)Environmental educationService (business)Wildlife
DOInot available

Abstract

fetched live from OpenAlex

On August 19, 1997, the Canadian Wildlife Service an-nounced that the use of lead shot will be prohibited for the harvesting of migratory game birds, nation-wide, begin-ning on September 1, 1999. This paper presents some use-ful information with respect to the spent lead shot issue, as well as its most common replacement steel, and takes a ho-listic viewpoint. Hands-on activities are introduced that can be used at the elementary or secondary school level. The spent lead shot issue is a topical environmental education issue of particular interest to rural Canadians and Native North Americans for social, cultural, and economic reasons. The non-toxic shotshell issue will remain topical because concerns have been raised about the safety of substitutes, other than steel, with respect to the environment and hu-man health. Résumé Le 19 août 1997, le Service canadien de la faune a annoncé qu’à partir du premier septembre 1999, l’usage des carabines à plomb serait défendu pour la chasse aux oiseaux migratoires, dans les réserves, à travers tout le pays. Cet article présente une information pertinente quant à la controverse des carabines à plomb ainsi qu’à son outil de remplacement, à savoir l’acier. Des activités expérien-tielles pour le primaire et le secondaire sont proposées. La controverse des carabines à plomb est un sujet d’intérêt en éducation relative à l’environnement, plus particulièrement

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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
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
Published2016
Admission routes1
Has abstractyes

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