Storying Ways to Reflect on Power, Contestation, and Yarning Research Method Application
Bibliographic record
Abstract
Internationally within academia settler-colonial processes occur in various ways alongside a growth in the use of research methods conceived with Indigenous knowledges. However, most research environments and practices are built upon and privilege dominant non-Indigenous settler-colonial knowledge systems. It is within this power imbalance and contested space that Yarning research method is being applied and interpreted. Underpinned by an Indigenous Research Paradigm, we employed storying ways to examine researcher experiences of settler-colonialism and the Yarning research method. The story outlines challenges and pitfalls that researchers can fall into and critically examines how researchers can fail to recognise the depth of Indigenous knowledge embedded within the practice. This story is gifted by creating an imagined narrative interview with a character called Settler-Colonisation, whereby we identify a litany of settler-colonial processes impacting Yarning research. Scrutinising the epistemological and methodological practices and processes enacted in academia is imperative for better-informed application of Indigenous research methods and create sustainable research more generally.
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 | 0.036 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".