Bibliographic record
Abstract
My journey to better understand and to live my own WSÁNEĆ legal tradition has always been both complex and incredibly rewarding. This journey has, at times, also come with its challenges and tensions, including through law school and academia. Through the use of story I reflect upon this path of learning, and many of my own thoughts and experiences along the way. I have learned, and continue to learn, from many different people along this path, and I am so grateful to each of them. While this story is primarily a self-reflection, the themes and tensions that the character of this story (Cedar) embodies may resonant with many Indigenous people. These themes include family, community, place, identity, stories, law and culture. Each of these themes comes together and to life in this story through lived experience and my own empowering moments of living and coming to better understand WSÁNEĆ law. Ultimately, writing this story helped me in a moment when I needed it. My hope is that you too can find something helpful and rewarding within this story, and that you can use that along your own path.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".