Lenette, C. (2022). Participatory action research: Ethics and decolonization. Oxford University Press.
Bibliographic record
Abstract
The author sets the stage for this book with a beautifully articulated Preface stating her positionality, context, and intention for writing this book.In doing so, the author models many aspects of Participatory Action Research (PAR) and its complexities through her writing, with hopes of better preparing new and experienced participatory researchers.Lenette wrote this book during the COVID-19 pandemic and sought to use her privilege and scholarship to make a compelling case for PAR as a viable, yet messy, methodology for social justice research, decolonizing research practices, and policy change.The book is provocative, disruptive, and uncomfortable.I believe this is what the author intended.That said, the book is very informative, thought-provoking, and relevant for participatory researchers.The straight-talk approach was jarring at times, and refreshingly upfront.PAR may be perceived as a 'feel-good' methodology that takes a relational and collaborative approach between the researcher and co-researchers to enact change for the betterment of humanity, but there are challenges, biases, and obstacles that must also be recognized.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: no | Not applicable | low |
| gpt | Insufficient payload (model declined to judge) Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.085 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".