MétaCan
Menu
Back to cohort
Record W7062584453

Urban forest management planning: A case study of municipalities in Southern Ontario

2023· other· en· W7062584453 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2023
Typeother
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsBrock University
Fundersnot available
KeywordsUrban forestSustainabilityForest managementUrban planningUrban sustainabilitySustainable forest managementUrban forestryUrban management
DOInot available

Abstract

fetched live from OpenAlex

This current study reviews urban forest management planning in Ontario through a sustainability lens. After clarifying key terms and concepts in the field of urban forestry, the paper moves towards an analysis of two urban forest management plans from municipalities in Ontario. This analysis was accomplished using a qualitative content analysis approach, where the content from two urban forest management plans was assessed against a framework that defines core principles of sustainable urban forest management. Key insights from this analysis are then identified and used to present a framework the Town of Lincoln can follow to develop an UFMP for their urban forest. The findings from this study found that municipalities have a strong desire to achieve sustainable urban forest management, but external challenges and internal limitations present barriers to achieve this.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.671
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.191
Teacher spread0.176 · 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