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Record W7040032229

New Social Media, Risk Communication, and Wildlife Health: Implications for Indigenous Communities of Saskatchewan and Alberta, Canada

2014· dissertation· en· W7040032229 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2014
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousWildlifeFocus groupChronic wasting diseaseTraditional knowledgeRisk assessment
DOInot available

Abstract

fetched live from OpenAlex

The study involved Indigenous communities of Saskatchewan and Alberta which are adversely impacted by industrial activities in their traditional territory. The overall goal of this study is: the assessment of social media in risk studies among Indigenous communities of western Canada. The methods used were: interviews, focus group discussion (FGD), and net-mapping. Results showed that the majority of youths communicated around risk using new social media (NSM) in event of risk outbreak, while Indigenous Elders, communicated face-to-face and via cell-phone. Results also showed that youths use Traditional Knowledge learnt from the Elders to understand Chronic wasting disease (CWD) risk, interpret, communicate and mobilize around mitigation. The study concluded that the use of NSM is becoming increasingly important for scoping information around wildlife decline and emergency in these Indigenous communities.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.054
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0140.003
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.218
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 designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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