Call for reimagining institutional support for PAR post-COVID
Bibliographic record
Abstract
Although we believe academic researchers have a critical role to play in transformative systems change for social and ecological justice, we also argue that academic institutions have been (and continue to be) complicit in colonialism and in racialized, patriarchal capitalism. In this essay, we argue that if academia is to play a constructive role in supporting social and ecological resilience in the late stage Capitalocene epoch, we must move beyond mere critique to enact reimagined and decolonized forms of knowledge production, sovereignty, and structures for academic integrity. We use the pandemic as a moment of crisis to rethink what we are doing as PAR scholars and reflect on our experiences conducting PAR during the pandemic. A framework is presented for the reimaging of institutional support for the embedding of scholars in local social systems. We propose an academy with greater flexibility and consideration for PAR, one with increased funding support for community projects and community engagement offices, and a system that puts local communities first. This reimagining is followed by a set of our accounts of conducting PAR during the pandemic. Each account begins with an author's reflection on their experiences conducting PAR during the pandemic, focusing on how the current university system magnified the impacts of the pandemic. The author's reflection is then followed with a “what if” scenario were the university system changed in such a way that it mitigated or lessened the impacts of the pandemic on conducting PAR. Although this framework for a reimagined university is not a panacea, the reliance on strong in-place local teams, mutually benefiting research processes, and resources for community organizations putting in the time to collaborate with scholars can overcome many of the challenges presented by the pandemic and future crises.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".