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Record W7005222818

Property Rights in a Canadian Mountain Watershed: A Case Study from the Columbia River Valley, British Columbia

2010· article· en· W7005222818 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Library Of The Commons Repository (Indiana University) · 2010
Typearticle
Languageen
FieldMedicine
TopicSkin Diseases and Diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsProperty rightsCommonsResource (disambiguation)SustainabilityLand usePrivate propertyLand tenurePublic propertyCommon-pool resource
DOInot available

Abstract

fetched live from OpenAlex

"In the summer of 1995, an interdisciplinary team investigated property rights and biophysical aspects of sustainability in and around the village of Nakusp, B.C., in the Canadian Cordillera. A temporal review of land use was used to bring together historical trends of resource exploitation, overlapping property rights and evolving pressures for land use change. Community interviews, site observations and an extensive literature review were supported by analysis of satellite imagery, air photos, and biogeophysical resource maps within a Geographic Information System. Due to the history and culture of resource exploitation in the area, rights and 'rules' of land use, defined and practiced locally in the watersheds of the Columbia River valley, basically fall under state property and private property regimes. Although Canadian resource exploitation is highly articulated in law, it was found that there is an undertone of public participation at all levels. Strictly speaking community-level institutions are weak and poorly defined and the only local common property institution concerned mushroom gathering in the forest. At the regional scale, however, 'common-property'-like structures are evolving as a result of extensive public participation and stakeholder consultation concerned with future land use regulations. In comparison with the Kullu Valley mountain forest commons, the Nakusp area has an evolving strength in regional commons institutions. The comparison raises the question, 'Are local and regional institutions for the commons complementary or competitive?'"

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.437

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0210.004
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.164
Teacher spread0.159 · 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 designQualitative
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

Citations0
Published2010
Admission routes1
Has abstractyes

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