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Record W2024141391 · doi:10.5558/tfc79110-1

Forest and community sustainability – An Ontario perspective

2003· article· en· W2024141391 on OpenAlexvenueaboutno aff
Gord Miller

Bibliographic record

VenueThe Forestry Chronicle · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityGeographyPopulationBiodiversityEnvironmental resource managementWildlifeLand useEnvironmental planningCommunity forestryEcologyForest managementForestry

Abstract

fetched live from OpenAlex

Challenges to the sustainability of communities in northern and central Ontario are both ecological and socio-economic in nature. Ecological challenges include persistent impacts such as acid deposition as well as emerging challenges such as the advance of forestry northward and its impact on wildlife populations. Socio-economic challenges of the communities in this region include a declining population level as well as a workforce that is aging. Despite these challenges, northern communities, and forestry planners in particular, have knowledge and experience of value to community planning throughout Ontario. Examples include the fact that foresters and forestry-based communities know how to plan at the landscape ecosystem level, integrate biodiversity conservation and decide on the long-term disposition of land. This knowledge could make a significant contribution to community sustainability in southern Ontario communities, and inadvertently enhance the credibility and influence of forest planning methods and foresters in urban centres. Key words: sustainability, Environmental Commissioner, land use, forest, caribou, ecology, population

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.670
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.228
Teacher spread0.204 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2003
Admission routes2
Has abstractyes

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