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Record W6888909957 · doi:10.25316/ir-19773

Social Investigation of Management Approaches to Effectively Control Scotch Broom (Cytisus scoparius) Invasion in the Sooke Region of Vancouver Island, BC

2024· dissertation· en· W6888909957 on OpenAlexaboutno aff

Bibliographic record

VenueVIUSpace (Vancouver Island University Library) · 2024
Typedissertation
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBroomInvasive speciesEcosystem managementBiodiversityControl (management)ObstacleEcosystem services

Abstract

fetched live from OpenAlex

Invasive plant species, particularly Scotch broom (Cytisus scoparius), pose significant threats to biodiversity and ecosystem services on Vancouver Island by obstructing native plant restoration and elevating wildfire risks. This study investigates social perspectives on management strategies for Scotch broom control in the Sooke Region through key informant focus group discussion and an online community survey. The analysis identified significant challenges in disposal management, including high costs, limited funding, and regulatory gaps. Participants from both groups emphasized the need for enhanced community engagement and comprehensive invasive species policies. The primary obstacle to effective management was found not to be removal methods—chemical, biological, or mechanical—but an inadequate regulatory framework that lacks sufficient disposal management and support. Establishing a clear regulatory framework for invasive species management is essential for successful control and ecosystem restoration. This study offers evidence-based recommendations to improve management practices in the region and potentially other jurisdictions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.194
Teacher spread0.179 · 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.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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