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Record W4391814040 · doi:10.33002/enrlaw-04

Environmental, Legal and Social Implications of Aggregate Extraction (Mining) Operations

2024· book· en· W4391814040 on OpenAlexaboutno aff
Tony Sevelka

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsRock blastingEngineeringNarrativeEnvironmental planningGeographyMining engineering

Abstract

fetched live from OpenAlex

The book "Environmental, Legal and Social Implications of Aggregate Extraction (Mining) Operations" takes a comprehensive look at the multifaceted impact of mining activities on the environment, legal frameworks, and social dynamics. The narrative unfolds layer by layer, examining the intricate connections between aggregate extraction operations and their consequences. Beginning with an introduction that sets the stage for the exploration ahead, the book addresses the environmental concerns associated with blasting quarry operations. It delves into issues of land use compatibility and potential impacts on property values, offering a detailed analysis of the complex relationship between mining activities and the surrounding landscape. Legal dimensions take centre stage in subsequent chapters, shedding light on adverse and cumulative effects of blasting quarry operations. The book explores lawsuits and complaints arising from such activities, presenting a thorough examination of the legal battles that often ensue. Proposed remedies are also discussed, aiming to navigate the challenges posed by the intersection of mining and legal frameworks. Safety considerations are highlighted in the discussion on preventing the potentially deadly consequences of flyrock. The book advocates for mandatory minimum setbacks and separation distances, addressing the need for proactive measures to ensure the safety of both workers and nearby communities. Scientific aspects of mining operations are scrutinized in detail, particularly the reliability of flyrock throw calculations. The narrative points out the unscientific and unreliable nature of current methodologies, emphasizing the ongoing challenges in accurately predicting and mitigating the impacts of flyrock incidents. Real-life cases add a human dimension to the exploration, with a focus on thirteen homeowners living near a blasting quarry. The book details their experiences, including buyouts initiated by quarry owners, providing a personal perspective on the social implications of mining activities. A specific regional focus on Ontario brings attention to the sterilization of homeowners' land and the subsequent loss of property value. The book frames these occurrences as a de facto taking without compensation, raising ethical and legal questions about the toll of aggregate extraction on local communities. In its conclusion, the book synthesizes insights from the preceding chapters, emphasizing the delicate balance required in aggregate extraction operations. It prompts reflection on the need to harmonize economic interests with environmental sustainability, legal compliance, and social well-being. "Environmental, Legal and Social Implications of Aggregate Extraction (Mining) Operations" serves as a thought-provoking and comprehensive exploration, offering readers a nuanced understanding of the challenges posed by mining activities and advocating for responsible practices in the industry.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.007
Scholarly communication0.0090.004
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.010
GPT teacher head0.221
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
Published2024
Admission routes1
Has abstractyes

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