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Record W4236683592 · doi:10.5558/tfc80002-1

EDITORIAL / ÉDITORIAL

2004· article· fr· W4236683592 on OpenAlexvenueaboutno aff

Bibliographic record

VenueThe Forestry Chronicle · 2004
Typearticle
Languagefr
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyEnvironmental science

Abstract

fetched live from OpenAlex

Traditionally, forest management meant providing wood to satisfy industrial and human needs, such as shelter, fuel and food.In Canada, for more than a century, the conservation of fish, deer, birds and other wildlife and their habitats has been the driving force in managing forests for purposes other than wood products.Modern societies are now concerned with the provision of multiple forest values (i.e., social, cultural, environmental, economic) based on sustainable forest management.Moreover, we have also recently begun to consider the value of ecological services (i.e., clean air and water) as an additional contribution of forested ecosystems to the well-being of our societies.Of the multitude of values derived from forests, ecological services may be one of the most difficult to communicate to the public as the benefits are not as obvious as those of other forest values.Problems with ecological services become more evident only when critical thresholds have been reached, provoking significant detrimental effects to the landscape, such as flooding and erosion.Canada has played a leadership role in developing policies and instruments to support, and measure our progress with respect to sustainable forest management.The criteria and indicators that were developed via the Canadian Council of Forest Ministers in the mid-1990s have been instrumental in moving sustainable forest management from a basic concept to a measurable management approach.The criteria and indicators can be used to measure the integrity of wildlife habitats and biodiversity.These measures provide a means for governments and private corporations to assess their effectiveness at managing forests sustainably, and to adapt their policies and/or operating practices to improve their performance.Canadians have also come to realize that our immense country and forested habitats are part of the global ecosystem.The impacts of global climate change, for example, have begun to become more concrete with the significant fluctuations in weather regimes.Invasive species, such as the mountain pine beetle that were typically hampered by cold winter temperatures, have thrived in the mild winter conditions of the past few years in British Columbia and have caused severe lodgepole pine mortality.As well, warmer and drier summers are considered to be a major contribution to the increase in forest fires across the country.In a similar global way, Canada is now exposed to new marketplace factors.Access to domestic and international markets is increasingly dependent on a company being certified to internationally recognized standards, or to specific standards developed by foreign clients of our forest products.Therefore, companies and forest managers in Canada must operate in consideration of global economic and social standards to be successfully competitive.With regard to the management of Canada's forests, international public opinion indicates that strong concerns exist for the protection of biodiversity, carbon sequestration, and the rights of Aboriginal peoples.These three values are, in fact, the focus of the Climate Change Protocol and the Convention on Biological Diversity, both of which are international conventions that have been ratified by Canada.Due to the complexity of these values, selected indicators are commonly used to evaluate forest management practices and Canada's fulfillment of our international obligations under these con- E D I T O R I A L

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)0.003
metaresearch head score (Gemma)0.024
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.182
Threshold uncertainty score0.610

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0070.004
Open science0.0030.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.1820.133

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 head0.008
GPT teacher head0.236
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 designNot applicable
Domainnot available
GenreEditorial

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
Published2004
Admission routes2
Has abstractyes

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