Crossing Many Boundaries in Creating Allies: Personal Encounters to Unfolding Science to Privilege Indigenous Knowledge
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper discusses the challenges and experience of two faculty members (one Inuit, one White) as they seek to aid each other in fulfilling the institutional tenure track and program demands made upon them and as they seek to address how to engage teacher candidates in Indigenous knowledge and anti-racist education. There is discussion of practical action and resources for teaching anti-racism through privileging Indigenous knowledge and “unfolding” Eurocentric science, and of the ethical and philosophical challenges and what transpires in negotiating the individual and ethno-cultural difference of each faculty member through an Indigenous gaze (Ermine, 2007). ota masinahikanis masinahâmok tânisi e-ki-isi-âyimihocik oki niso ataskeskesak (peyak ayaskimow, peyak wâpiski-wiyâs) ekwa mina tânisi e-isi-wicihitocik oma kâ-masinahikehecik ekwa mina ohi kiskinwahamâkana tânisi ka-isi-kiskinwahamawâcik iyiniw-kiskihtamowin ekwa namoya ka-pakwâtitohk. mâmiskocikahtew tânisi ka-isi-atoskahtâkik oma namoya ta-pakwâtitohk âpacihtâtwawi kihci-iyiniw-kiskihtamowin ekwa mina ka-taswekinamihk moniyawipinikewin ekwa ta-kwe-miyo-wipinike mâka ka-ahkâm-mâmawi-atoskâtamihk poko soskwâc pakwâweyak ta-iyiniw-wâpahtekowisit.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it