Carrying the Torch Forward: Indigenous Academics Building Capacity through an International Collaborative Model
Bibliographic record
Abstract
This article describes an ongoing international collaboration regarding Indigenouslanguage and culture education that engages post-secondary institutions in Hawai'i,Arizona, Alaska, New Zealand, and Canada. Formed in 2005 under the leadershipof the late William Demmert, Jr., this community presently brings a critical mass ofprominent Indigenous and non-lndigenous scholars together with emerging Indigenous faculty and students using hybrid delivery—virtual and face-to-face interaction—for internationally conducted coursework. Topics on Indigenous epistemology,language, culture, knowledge, traditions, and identity are the focus of two rotatingIndigenous education course themes: Indigenous culture-based education and Indigenous well-being through education. Through networking and collaboration, theseminar has created "free spaces for authentic voices " (Gilmore, 2010), and mentorship of emerging Indigenous faculty and scholars to step into the role of leadershipin academic arenas, a process we refer to as “carrying the torch forward. ” Througha reflective review that included input from site instructors and student voices, theco-authors, who are Indigenous faculty, scholars, as well as former students, discussthe impacts of engaging the academy with Indigenous knowledges, peoples, and communities in meaningful ways. In this paper, we reflect on and highlight the potentialthat such collaborations provide, to access academic power while supporting the responsibility that Indigenous students assume in navigating the pathway of highereducation toward Indigenous self-determination, broadly. More importantly, the international seminar space allows for advancement of this endeavour, grounded inthe Indigenous values of responsibility, respect, relevance, reciprocity, relationships,and resiliency.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.027 | 0.040 |
| Scholarly communication | 0.028 | 0.029 |
| Open science | 0.005 | 0.037 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".