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Record W2981983714 · doi:10.4095/299773

How to build a living city - balancing the needs of human development and ecosystems

2017· report· en· W2981983714 on OpenAlexaboutno aff
Donald H. Ford

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsEcosystemFundamental human needsEnvironmental resource managementBusinessEnvironmental planningGeographyEcologyEnvironmental scienceBiologyPsychology

Abstract

fetched live from OpenAlex

Conservation Authorities are unique to the province of Ontario. They are local, non-profit environmental organizations that are empowered to regulate development and activities in or adjacent to river or stream valleys, Great Lakes and inland lakes shorelines, watercourses, hazardous lands and wetlands. The Conservation Authorities Act, passed in 1946, provides the legislative backbone for their existence. Funding is provided through a combination of municipal and provincial support, permit and service fees and charitable donations. Toronto and Region Conservation serves a population of more than 4,000,000 people in a jurisdiction that covers more than 2400 km2. We receive development applications for over 1000 projects per year. These files include engineering and hydrogeologic reports prepared on behalf of the development proponents that often downplay the potential impacts of their projects to the natural environment. Our role as hydrogeologists is to critically review these reports and determine if reasonable conclusions have been made based on reliable data. For hydrogeology, we consider both temporary and permanent dewatering, pre- and post-development water budgets, and consumptive groundwater use. We must then communicate our findings in clear, simple language to our in-house planning team, proponents, and sometimes members of the public. All this is done in a framework of limited funding and challenging timelines. We meet these challenges through the use of conceptual and numerical models developed in partnership with neighbouring conservation authorities and our municipal partners. These regional model results are then shared with development consultants to facilitate continuous improvement from their studies completed at the site scale. To continue to advance our hydrogeologic understanding, we also work with subject matter experts at the provincial and federal levels of government, and are working at integrating climate change into our models. This presentation will summarize some of our successes and failures over the past 15 years and provide insights to similar organizations responsible for protecting and enhancing our natural environment.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.633
Threshold uncertainty score0.738

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.011
Scholarly communication0.0100.007
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.006

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 head0.024
GPT teacher head0.252
Teacher spread0.228 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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