Bibliographic record
Abstract
As an Assistant Professor in Community Economic and Social Development (CESD) at Algoma University College, Ontario, Canada and a member of Asopricor Holistic Association, Cundinamarca, Colombia, respectively, the authors have engaged in an ongoing dialogue regarding the inherent contradictions of forming a North—South, university—community research collaboration. For those who have engaged in and/or read about action research, the questions addressed in this article are familiar: How can we maintain respectful relations between us? How can we ensure the project respects local knowledge? How can we ensure the ownership of the new knowledge created by the project remains with the collective? How can we balance the power dynamics between ourselves, and between the organizations involved? What the article offers, is a dialogical reflection on how these challenges are being met within this particular project. It examines the development of a common set of values and beliefs that emerge as the researchers attempt to engage within the `ethical space' (Ermine, 2005) necessary for the development of a respectful collaboration. The article explores and develops a series of questions for researchers to consider as they struggle to find common ground where such an exchange, crossing cultural and power divides, can occur.
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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.026 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.025 | 0.021 |
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".