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Record W2088424294 · doi:10.2166/wst.2006.312

Evaluating characteristics of community riparian awareness program interactions

2006· article· en· W2088424294 on OpenAlexaboutno aff
Norine Ambrose, Lyle C. Fitch, Nancy G. Bateman

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsRiparian zoneBusinessMandateVariety (cybernetics)Knowledge managementEnvironmental resource managementWatershed managementPsychologyPublic relationsMedical educationComputer scienceWatershedPolitical scienceMedicineEcologyHabitat

Abstract

fetched live from OpenAlex

As part of its mandate to evaluate and monitor program delivery, the Alberta Riparian Habitat Management Society (Cows and Fish) has commissioned independent evaluations to examine the effectiveness and applicability of the community-based riparian awareness and management program. The society's aim is to improve the understanding of landscape function, to better enable landowners and managers to make management decisions. The staff interaction evaluation examined staff ability to deliver certain valued characteristics, and identified whether the program and staff increased awareness and management action. Respondents rated staff highly on all characteristics. Landowners that participated in riparian health programming as part of community/watershed groups were 19% more likely to have learned new information and 21% more likely to implement management change than those that were not part of a group. Repeat interactions are critical to learning new information and influencing management. All those with frequent interactions had learned new information, compared to only 70% of those with very little interaction. A diverse array of interactions led respondents to alter their management, indicating the need for a wide variety of extension tools and activities. The results strongly support the need for a community-based approach in resource management and awareness activities, which enables repeat, ongoing and diverse interactions with extension staff.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.321
Teacher spread0.288 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2006
Admission routes1
Has abstractyes

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