Living Together v. Living Well Together: A Normative Examination of the SAS Case
Bibliographic record
Abstract
The European Court of Human Rights decision in SAS from France illustrates how a policy and national mantra that ostensibly aims to enhance inclusiveness, ‘living together’, is legally deployed in a manner that may have the opposite effect. In essence, despite acknowledging the sincerity of SAS’s religious practice of wearing the niqab, and her agency in making the decision to do so, the Court focuses on radicalism and women’s oppression amongst Muslims. Taking the notion of living together as the beginning point, the paper explores the normative assumptions underlying this notion as illustrated in the judgment of the Court. An alternative approach, drawing on the work of Derrida for the notion of ‘living well together’ will be proposed and its implications for social inclusion explicated. The paper’s aim is to move beyond the specific example of SAS and France to argue that the SAS pattern of identifying particular values as ‘national values’, the deployment of those values through law, policy and public discourse, and their exclusionary effects is playing out in a number of Western democracies, including Canada, the country with which the author is most familiar. Because of this widespread dissemination of values and their framing as representative of who ‘we’ are, there is a pressing need to consider the potentially alienating effects of a specific manifestation of ‘living together’ and an alternative model of ‘living well together’.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.034 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".