Bibliographic record
Abstract
I have lived in Mohkínstsis/Calgary for four years, most of which have been marked by the pandemic that is ongoing as I write this. I highlight this here because my physical, social, and cultural connections with this city are limited. However, given the circumstances, I had the privilege and opportunity to connect with the land and the non-human world around me. Walking, a privilege that allowed me to engage with places I have visited and lived in throughout my life, has been particularly significant during the pandemic. Walking through the northwest suburbs of this city has allowed me to foster a relationship with the land, which now animates my practice. In the spirit of respect, reciprocity, and truth, I acknowledge that I am an uninvited white settler occupying this land, which forms the traditional territories of the Blackfoot Confederacy (Siksika, Piikani, Kanai First Nations), the Tsuut’ina First Nation, and the Stoney Nakoda (Chiniki, Bearspaw, and Wesley First Nations). This territory is also home to the Métis Nation of Alberta, Region 3. I am grateful to be situated here, and through my work, I aim to honour the land and all its forms, taking greater responsibility for my presence and potential future in this place.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.012 |
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".