MétaCan
Menu
Back to cohort
Record W2914391304

Maintaining my ally relationships from afar

2018· article· en· W2914391304 on OpenAlexaffabout
Brian Beaton

Bibliographic record

Venue2018 Conference of the Canadian Society for the Study of Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGeneral partnershipWork (physics)Public relationsPolitical scienceEconomic growthEngineering
DOInot available

Abstract

fetched live from OpenAlex

Remote First Nations across Canada face many challenges related to the provision of quality education and training programs for local citizens. First Nations across northwestern Ontario are using digital technologies and broadband infrastructure to deliver a full range of education and provide training opportunities for formal and informal learning for their citizens. This paper examines my research and policy development work and relationship with remote First Nations as a result of a long-term partnership. Community surveys conducted in 2014 and 2016 and follow-up interviews of residents in five remote First Nations were completed exploring online teaching, education, and professional development opportunities available and what their experiences are with these opportunities. The data also examines the programs, support systems and online services remote community residents desire. Follow up data was collected in 2015 and 2016 during community visits to one of the remote communities. Through a settler colonialism lens and action research approach, I present the importance of supporting First Nation control of their education systems and delivery systems through research and appropriate First Nation-led policy development work supporting services and innovative opportunities in remote 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 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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.119
GPT teacher head0.330
Teacher spread0.211 · 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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venue2018 Conference of the Canadian Society for the Study of EducationSame topicService-Learning and Community EngagementFrench-language works237,207