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Record W4243116396 · doi:10.15402/esj.2015.1.a03

Community Engagement in the Humanities, Arts, and Social Sciences: Academic Dispositions, Institutional Dilemmas

2015· article· en· W4243116396 on OpenAlexvenueaboutno aff
Sara Dorow, nicole Smith Acuña

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Agency (philosophy)Public relationsResource (disambiguation)Community engagementCitizen journalismPolitical scienceCommunity developmentSociologyVariety (cybernetics)Participatory action researchThe artsLibrary scienceGeographySocial science

Abstract

fetched live from OpenAlex

In April 2014, McMaster University and Carleton University collaborated with Kugluktuk, an Inuit community in Nunavut to survey community views on resource development and produce a larger community report. This was part of a Community Readiness Initiative (CRI) piloted by the Canadian Northern Development Agency (CanNor) to assess the socio-economic needs of communities across the North prior to mine development. Kugluktuk is the first of seven communities across Nunavut, the Northwest Territories, and the Yukon to produce their final report. Universities have started to play an important role in developing a ‘third mission’ whereby researchers are encouraged to collaborate with non-academic organizations. This collaborative approach can include contract research and consulting, as well as informal activities like providing ad hoc advice and networking with practitioners. Working as an academic in this environment can create tensions, but it can also create opportunities to foster and ensure meaningful input and consultation from a variety of stakeholders. This paper focuses in depth on the collaborative nature of the CRI process that began in April 2014 and ended in August 2015 with an emphasis on the community-based participatory research approach that we took. With insights that apply equally well outside of the Kugluktuk context, the approach that we took also provides a useful model for engaging with issues on mining and resource development opportunities.

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)0.895
metaresearch head score (Gemma)0.084
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8950.084
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.8960.003
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.601
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 head0.417
GPT teacher head0.461
Teacher spread0.043 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueEngaged Scholar Journal Community-Engaged Research Teaching and LearningSame topicIndigenous Health, Education, and RightsFrench-language works237,207