MétaCan
Menu
Back to cohort
Record W7054956876

Assessing stakeholder interests: a strategy for best management practices of free-roaming horses, Chilcotin, British Columbia

2010· dissertation· en· W7054956876 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2010
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYStakeholderTransparency (behavior)Best practiceWildlife managementStakeholder managementWildlifeSocioeconomic statusNatural resource management
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this research was to assess stakeholder interest pertaining to best management practices for free-roaming horses in the Chilcotin, British Columbia. The study site is located between the towns of Hanceville to the east and Tatla Lake to the west. A case study approach was adopted, utilizing on-site observation, document analysis and semi structured interview methods. Analysis, through the reduction and interpretation of data, allowed for the emergence of the themes and subthemes. Themes were free-roaming horse interaction with both the biophysical and socioeconomic landscape as well as management. British Columbia government, ranchers, First Nations and Non Governmental Organizations were interviewed on their awareness and interaction with free-roaming horses, the management and policies pertaining to the species. Free-roaming horses have historically represented a social and economic resource, although stakeholders have had little input into management decisions. Antiquated policies, clashing social values, changing land title and land use and difficult economic times have resulted in a lack of clarity regarding jurisdiction, and therefore management, for the free-roaming horses. Management goals are not clear due to lack of classification as livestock or wildlife under provincial or federal legislations. A strategy, which promotes decentralization, collaboration and transparency in decision and policy-making is recommended. Multi-stakeholder research is the first step toward creating such a strategy.

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)0.049
metaresearch head score (Gemma)0.042
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 score0.532
Threshold uncertainty score0.930

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.006
Science and technology studies0.0220.006
Scholarly communication0.0150.005
Open science0.0040.011
Research integrity0.0030.003
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 head0.043
GPT teacher head0.251
Teacher spread0.207 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)Same topicLaser Design and ApplicationsFrench-language works237,207