Bibliographic record
Abstract
As part of my Doctor of Education program, I was asked to study Dr. Marie Battiste’s (2017) book Decolonizing Education: Nourishing the Learning Spirit. In response to that assignment, I built a WordPress site as a way to experiment with crossing boundaries of physical and digital places, between different Indigenous knowledges and notions of teaching and learning. While building the site, I looked for localized examples of Battiste’s concepts and ideas among the Inuvialuit, the Indigenous group with which I am the most familiar, in what became an exploration of the wonderful work being done in the Inuvialuit Settlement Region to preserve the culture and decolonize ways of thinking. I knew some of these resources existed, but was surprised by the depth and variety of materials available. In this paper, I present that website as an experimental example of digital curation that stitches together the book, a series of digital artefacts found via Internet searches and my own reflections on those artefacts. While building it, I did not seek out answers but instead explored the possibilities of curation as a path to decolonization education. The resulting site design is both personal and incomplete. Through this process, I hope to open generative cracks that provoke new ways of thinking about digital curation as a means of supporting active engagement in the complicated and necessary conversations regarding decolonization.
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 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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".