Sterilization of Homeowners’ Land and Loss of Property Value Occasioned by Aggregate Extraction in Ontario: A De Facto Taking Without Compensation
Bibliographic record
Abstract
Aggregate extraction operations are notorious for causing significant environmental damage, often permanent and irreversible, and when permitted in the wrong geographic locations nearby property owners are adversely and uniquely impacted. Through no fault of their own conduct, innocent property owners near an aggregate extraction operation experience a diminished quality of life, lose the full use and enjoyment of their properties, and sustain a reduction in the value of their properties, for which no compensation is received. The unauthorized and free use of third-party property by a Pit or Quarry results in a de facto taking of an interest in land similar to an easement for as long as the Pit or Quarry remains operational, which, in Ontario, should be assumed to be in perpetuity. A Licence to extract aggregate has no expiry date, and annual tonnage figures are not publicly accessible. Given the indeterminate duration of aggregate extraction, municipalities need to develop robust land use policies that will protect existing communities, sustain orderly and efficient long-term growth and preserve the quality of life for future generations.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".