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Record W1568926488

Sustaining Old Growth Pinelands in Ontario: Pathways to Reform

2000· article· en· W1568926488 on OpenAlexaffabout
Jamie Benidickson

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCertificationForest managementLegislatureSustainabilityCitizen journalismSustainable forest managementEnvironmental planningPine barrensForestryEnvironmental resource managementGeographyPolitical scienceEcologyEnvironmental scienceArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Controversy over old growth pine forests in Ontario and consideration of related forest management issues associated more generally with sustainability encouraged a range of reform initiatives. The proposals might be broadly clustered under four headings: (a) legislative change; (b) participatory and procedural innovations affecting decision-making processes; (c) non-governmental initiatives — notably forest certification programmes; and (d) education and other measures within the profession of forestry. None of these approaches provided a conclusive resolution of the old growth controversy, although as a result of the Lands for Life/Our Living Legacy process significant areas of old growth pine will enjoy some form of protection. Despite these changes, forest management decision-making relating to old growth values will continue to require the ongoing exercise of discretionary authority as described in a companion essay. (Forest Management and Environmental Values: Ontario's Old Growth Pinelands. Available on the SSRN http://ssrn.com/abstract=2287478).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.006
GPT teacher head0.201
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2000
Admission routes2
Has abstractyes

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