Bibliographic record
Abstract
Even though the notion of “disability” has received ongoing critical scrutiny and re-imagination within the field of disability studies, the concept of law has often been taken for granted. Although people with intellectual disabilities figure as subjects of legal discourse, seldom are they presented as participants in it. I argue that this owes to assumptions about law that fail to recognize the diversity of ways human beings exercise agency and experience normativity. I believe that research on the relationship between “law, religion, and disability” stands to benefit from imagining law as an interactional, symbolically plural human endeavour. I build on the theoretical framework of critical legal pluralism to highlight how law arises through interaction – informally and implicitly, as well as officially and explicitly. Drawing on fieldwork I carried out in L’Arche Montréal – a faith-based community serving people with intellectual disabilities – I illustrate the creative role that people with intellectual disabilities play in the construction of legal normativity. As important as it is to ask how law affects people with intellectual disabilities, is to ask about how their actions also shape law. When it comes to asking what law means for some of the most vulnerable members of society, it is not just a question of seeing how it may function either to prevent or to remedy harm. It is also a matter of seeing the ways in which law may facilitate (while being forged by) the cultivation of relationships and the liberation of human potential.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.056 | 0.109 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".