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Record W2605299539 · doi:10.1139/cjss2010-033

Regulatory history of Alberta's industrial land conservation and reclamation program

2012· article· en· W2605299539 on OpenAlexaffabout
Chris Powter, N. R. Chymko, Gordon Dinwoodie, Darlene Howat, Arnold Janz, Ryan Puhlmann, Tanya Richens, Don Watson, Heather Sinton, Kevin Ball, Andy Etmanski, Bruce D. Patterson, Larry Brocke, Ralph Dyer

Bibliographic record

VenueBioOne Complete (BioOne) · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsAlberta Environment and Protected AreasUniversity of Alberta
Fundersnot available
KeywordsLand reclamationEnvironmental scienceEnvironmental protectionGeographyArchaeology

Abstract

fetched live from OpenAlex

Powter, C. B., Chymko, N. R., Dinwoodie, G., Howat, D., Janz, A., Puhlmann, R., Richens, T., Watson, D., Sinton, H., Ball, J. K., Etmanski, A., Patterson, D. B., Brocke, L. K. and Dyer, R. 2012. Regulatory history of Alberta's industrial land conservation and reclamation program. Can. J. Soil Sci. 92: 39-51. Alberta first legislated the requirement to reclaim land disturbed by industrial activities in 1963 with the enactment of the Surface Reclamation Act. In 1973 the Land Surface Conservation and Reclamation Act introduced the concept of conservation and added new regulated industries and an approvals process. In 1993 the Environmental Protection and Enhancement Act linked reclamation and remediation in a single Act. Alberta's industrial land conservation and reclamation program developed over 48 yr from an initial focus on surface debris removal and safety to increasing emphasis on returning ecological function and minimizing cumulative effects. The program has been influenced by various factors, includingregulatory policies and objectives, education and expectations of stakeholders and the public, educational background and expertise of regulators, advances in science, technology and industry practices, type and scale of land disturbances, intended post-reclamation land use, and working with partners. Vigorous discussion and debates on productivity vs. capability, reclamation vs. restoration, reclamation vs. remediation, conservation vs. reclamation, land vs. water and scientific possibilities vs. practical realities have shaped the program's direction. This review will provide insights for other jurisdictions dealing with the need to balance industrial development and environmental protection in the face of growing public awareness and scrutiny.

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)0.012
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.421

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0060.003
Scholarly communication0.0060.001
Open science0.0050.002
Research integrity0.0040.003
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 head0.371
GPT teacher head0.220
Teacher spread0.151 · 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

Citations20
Published2012
Admission routes2
Has abstractyes

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