Engaged Queer Scholarship: Probing a New Paradigm of Knowledge Creation
Bibliographic record
Abstract
This article features a reflexive iteration of engaged scholarship regarding the Queer Liberation Theory Project, a community-based research study with the social justice group Queer Ontario, which involves academics, activists, and artists, a number of whom are cross affiliated. We explore the tensions and challenges involved in developing and creating knowledge via an engaged scholarship process that must respect the historical philosophical perspectives of a social movement as well as today’s academic theories. This article addresses the challenges of developing new knowledge (a theory) that counters a powerful, neoliberal, mainstream segment of today’s lesbian, gay, bisexual, and transgender (LGBT) movements, with implications for society at large. The layered issues associated with engaged scholarship are disentangled, including vulnerability to neoliberalism, navigating competing perspectives, and how academics/activists/artists both understand and engage in knowledge creation.
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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 | 0.136 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".