Revelations of a White Settler Woman Scholar-Activist: The Fraught Promise of Self-Reflexivity
Bibliographic record
Abstract
Based on a metanarrative analysis of the self-reflexive process I undertook during my research into the “solidarity encounter” between Indigenous women and White women in a contemporary Canadian context, I argue that self-reflexivity is a fraught mechanism for grappling with and dismantling structural privilege. I recount how, despite my best self-reflexive efforts and expectations to the contrary, I could not completely forestall some of the ways in which my subjectivity and hence power would infuse the research—specifically, in how the specter of the liberal subject would haunt it. This haunting, I contend, is indicative of the limits of self-reflexivity when it is underpinned by modernist/liberal ideologies of subjectivity. In short, I convey the perils and promises of self-reflexivity as a mechanism for revealing researcher impact on and for leveling power relations in social justice research (and beyond). Specifically, I identify in my own practice elements of the “validated reflexive strategies” critiqued by Wanda S. Pillow. I conclude that self-reflexivity is most valuable when approached as a window into structural oppression and privilege and not only into the power of researchers as individuals. Building on Sara Ahmed’s reflexive “double turn,” I argue that radical reflexivity is a better model for avoiding the vortex of a self-reflexivity performed by modernist/liberal subjects. I propose that radical reflexivity can assist researchers to identify the ways in which our structural positions overdetermine (though never absolutely or seamlessly) the contours of our scholarly and political commitments.
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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 | 0.028 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.032 | 0.086 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".