Bibliographic record
Abstract
Universities interpret their role in relation to engagement in several different ways. This chapter focuses on one of these, that is, research partnerships between academics and community organizations intended to address pressing social problems. Whilst these partnerships can themselves take a range of forms, this chapter argues that to be effective, researchers have to deal with not just the practical issues of how people participate in research but also issues of knowledge and power. Drawing on empirical examples from the UK and Canada, it highlights the significance of relational dimensions to these collaborations and the importance of trust, reciprocity and mutual benefit. It also identifies what could produce more epistemically just dynamics, critical for achieving more transformative engagement. In doing so, the chapter makes the case for meaningful ways in which the resources of the university can be connected to efforts for social transformation and offers practical ideas to researchers and engagement practitioners about how this can be achieved.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".