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Record W3025728272 · doi:10.15402/esj.v5i3.70365

Tenets of Community-Engaged Scholarship Applied to Delta Ways Remembered

2020· article· en· W3025728272 on OpenAlexaffvenueabout
Lalita Bharadwaj

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsScholarshipCompendiumStorytellingIndigenousEngaged scholarshipPromotion (chess)Public relationsSociologyNarrativePolitical scienceHistoryPoliticsLaw

Abstract

fetched live from OpenAlex

This essay reviews challenges posed to community-engaged scholars regarding tenure/promotion processes in Canadian universities, with a note to characteristics of community-engaged scholarship that were developed by Catherine Jordan (2007) to address gaps in academic assessment of engaged scholarship. These characteristics are: clear goals, adequate preparation, appropriate methods: scientific rigor and community engagement, significant results/impact, effective presentation/dissemination, reflective critique, leadership and personal contribution, and consistently ethical behavior. These are then applied to a non-peer reviewed work that describes the cumulative effects of environmental change for people in the Slave River Delta Region of the North West Territories, Canada. The reader is asked to view Delta Ways Remembered, a 13-minute video employing an enhanced e-storytelling technique to share and disseminate traditional knowledge about the delta from a compendium of people as a single-voiced narrative. The purpose is to highlight the scholarship underlying non-traditional academic expositions not readily assessed under current paradigms of academic evaluation. This essay strives to illustrate how Jordan’s characteristics can be applied to evaluate non-peer reviewed scholarly work, and also to share rewards and challenges associated with the harmonious blending of Indigenous and western knowledge addressing societal/environmental issues identified by the Indigenous community.

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)0.918
metaresearch head score (Gemma)0.820
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.9180.820
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.7250.001
Scholarly communication0.0020.001
Open science0.0040.002
Research integrity0.0010.859
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 head0.319
GPT teacher head0.414
Teacher spread0.094 · 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
DomainMethods
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
Published2020
Admission routes3
Has abstractyes

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