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
Several scholarly works have opened discourse around the complicity of non-White settlers in continuing the oppression of Indigenous Peoples through their ideological adoption of and material participation in White supremacist neoliberal capitalist structures, structures set in place through settler-colonial possibility (Chen, 2021; Pulido, 2018; Saranillio, 2013; Tuck & Yang, 2012; Upadhyay, 2016). This anti-colonial autoethnography (Laurendeau, 2023) attempts to add to this existing body of scholarship, by further considering the nuances and specificities of settler identities. More specifically, it is an exploration—without territorialization—of this author’s struggles as a racialized settler, scholar, and outdoor enthusiast involved in social justice work. In holding the twin rope tensions of being the subject of oppressive forces, while reinscribing oppression through these same forces, I attempt to engage in the on-going process of unsettling a settler self, as a means to support decolonization (Steinman, 2020).
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.017 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it