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Record W2319858471 · doi:10.1061/40737(2004)154

Dialogue on Adaptation to Climate Change in the Okanagan Basin, British Columbia, Canada

2004· article· en· W2319858471 on OpenAlexaffabout
Stacy Langsdale, Stewart Cohen, Rachel Welbourn, James Tansey

Bibliographic record

VenueCritical Transitions in Water and Environmental Resources Management · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsImpactUniversity of British ColumbiaEnvironment and Climate Change Canada
Fundersnot available
KeywordsClimate changeRecreationAgricultureGeographyStakeholderEnvironmental resource managementEnvironmental planningAdaptabilityPopulationPolitical scienceEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

The Okanagan Basin in south-central British Columbia is one of the most arid regions in Canada. Presently, water resources in the area are under stress due to recent population growth, intensification of irrigated agriculture and recreational activities, and extensive logging at higher elevations, leading to increased concerns about water quality and fish habitat. In addition the stressors listed, climate change impacts could alter water supply patterns significantly. A major focus of this research is to encourage the local community to consider climate change in their long-term water plans. Between November 2003 and February 2004, the research team conducted stakeholder workshops to evaluate water management and adaptation options. Participants investigated the local and regional adaptive capacity, determined preferred adaptive strategies, and identified economic, institutional, social, and political barriers to implementing these strategies. The results of these workshops will be presented.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.070
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0300.003
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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

Citations3
Published2004
Admission routes2
Has abstractyes

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