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Record W1592603279 · doi:10.22230/jem.2012v13n2a147

Field staff perspectives on managing climate change impacts in parks and protected areas.

2012· article· en· W1592603279 on OpenAlexaff
Pamela Wright

Bibliographic record

VenueJournal of Ecosystems and Management · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsClimate changeEnvironmental resource managementVulnerability (computing)HabitatDisturbance (geology)GeographyFocus groupClimate change adaptationEnvironmental planningEnvironmental scienceEcologyBusiness

Abstract

fetched live from OpenAlex

Within protected areas, the impacts of climate change have been the subject of discussion for over two decades. Reported impacts included changes to species and habitat distributions, sea level rise, glaciation and snow packs, hydrologic processes, and disturbance patterns. As part of a project to develop a long-term ecological change monitoring program for BC Parks that had a specific focus on climate change, a series of focus group interviews and an electronic survey of field staff were conducted. Field staff throughout the province reported observing a wide range of ecological and social impacts from climate change with projected increases in the future. Support for monitoring these impacts was strong as was invasive species removal. Findings illustrate the need for clarified policy and planning direction; habitat and species vulnerability assessments; education and experimentation with various mitigation and adaptation techniques; and implementation of a comprehensive monitoring program.

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)0.020
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.003
Scholarly communication0.0060.004
Open science0.0020.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0150.001

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 head0.023
GPT teacher head0.219
Teacher spread0.195 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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