Bibliographic record
Abstract
The following seeks to advance relational research methods by providing more specificity in how relationality is defined, and by engaging commonly held refrains on relational research. Responding to concerns about Indigenous relationality being pan-Indigenous, we suggest a three-part framework that defines Indigenous relationality. First, relationality as a defining aspect of global Indigeneity; second, relational understandings that emerge from specific Indigenous nations and third, relationality as manifest within inter-Indigenous connections. Building on our definitional work, we argue that three common refrains within relational research methods should be extended. First, researchers should be able to balance a slippage between the particular context of Indigenous nations and the general context of Indigenous relationality. Second, we have to do more than simply value relationships, and consider how we use relationality for critical thinking. Finally, ensuring accountability within Indigenous research requires us to revisit how we analyze the concept of community.
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 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 | 0.049 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 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".