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Record W2612510187

Perspectives on the Social, Economic and Environmental Impacts of All-season Roads in Two Remote First Nation Communities in Northern Ontario

2016· dissertation· en· W2612510187 on OpenAlexaboutno aff
Shayna Mihalus

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2016
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyEnvironmental planningEnvironmental resource managementEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

Remote Indigenous communities face a number of challenges associated with
\naccessibility. The development of all-season road corridors promises to solve some of
\nthese problems. However, changes to transportation can create many challenges.
\nSurveys and interviews conducted in two remote First Nations communities and
\nreported in this thesis reveal that community members are aware that both potential
\nharms and benefits from all-season roads will alter the communities? social wellbeing.
\nConcerns about negative potential impacts from all-season roads are triggered by past
\nexperiences and history. Fear may slow down progress of development in the Far North.
\nThese fears are associated with changes in the community and its surrounding landscape
\nincluding accessibility to drugs and alcohol, destruction of the land and disrespect from
\nnon-Indigenous people. While First Nation participants acknowledge that all-season
\nroads and increased access can produce or worsen negative impacts, they perceive the
\npositive outcomes, such as employment and community-to-community interaction, to be
\nworth the risks associated with all-season roads.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.311
Teacher spread0.266 · 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 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
Published2016
Admission routes1
Has abstractyes

Explore more

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