Metis Relationality of lii lway di la tayr through the teachings of interconnectedness and balance.
Bibliographic record
Abstract
The smell of smouldering ash, simmering stew, and sweet Medicines constantly filled the air all around me as a child.I was fortunate to grow up with a strong familial connection to the Land, so my understanding and relationality to lii lway di la tayr is quite strong.As a little one, my favourite snack was always fresh saskatoons picked right from the bush surrounding the Land of my grandparents. Our HomeMy grandparents built their house from the ground up.My mom told me stories about having to sleep in a tent at night while the house was being built during the day.They built a home, a successful farm, and eventually a mini-Metis history museum, plus so much more.I spent my summers growing up on the Land.Hiding and running through li traamb, the white poplar, with my cousins.Exploring the snowy fields upon snowshoes.Pretending we were little waposh, rabbits, racing one another.I remember the big bunches of sage hanging all around my Memere's kitchen.I loved harvesting willow branches with my mom so we could make dreamcatchers.In the early mornings of the summer, my cousins and I would walk around and pick bunches of wildflowers.Tasting the dew on the blades of grass for fun.We would surprise our Memere with colourful bouquets.From a young age, we were taught about the importance of tobacco, sage, cedar, sweetgrass, and so many more Medicines such as labrador tea and kinnikinnick.I had spent all of my holidays and celebrated my biggest achievements there.The Land my grandparents built their home upon was a meeting ground.It was filled with history and new beginnings.I could easily navigate through the Land surrounding us.I could tell you where the leeches would appear each spring.The giant rock on which my cousins and I found a sleeping bear once before.I could tell you which area was the best to find morel mushrooms in the spring and sage in the late summer.Sadly, as my grandparents grew much older, they had to sell their farm.To us, however, it was much more than that.It was the Land I once stamped my little feet upon.The home my family and I loved and cherished.I felt some sort of grief with the selling of their Land.I had to say goodbye to a part of our family, our history, and a part of me.My eldest child spent the earliest part of his childhood on the same Land.I remember the first time he walked down the path I once walked at the same age.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".