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Record W2515102308 · doi:10.1080/07900627.2016.1216830

Lessons from implementing integrated water resource management: a case study of the North Bay-Mattawa Conservation Authority, Ontario

2016· article· en· W2515102308 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Water Resources Development · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsNipissing University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStewardship (theology)MandateEnvironmental planningEnvironmental resource managementIntegrated water resources managementNatural resourceStakeholderStakeholder engagementNatural resource managementBusinessCommunity-based conservationWatershed managementWatershedWater resourcesPolitical scienceGeographyPublic relationsEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

This case study explores the North Bay-Mattawa Conservation Authority’s experience in implementing IWRM. Successes include protecting life and property by mitigating flood and erosion hazards; building capacity through multi-stakeholder collaborations; and fostering community stewardship. Ongoing challenges include limited resources and narrow mandate for addressing broader watershed and natural resources issues; and a need to enhance relationships with First Nations. The NBMCA has learned numerous lessons on how to apply IWRM, including collaborating early and often and fostering community stewardship.

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.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.274
Teacher spread0.250 · 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