Conscience and Cakes: Reaffirming the Distinction Between Institutional Duties and Individual Rights
Bibliographic record
Abstract
Abstract This article suggests that there may be scope to accommodate individual conscience whilst holding institutions to their full civil duties by making a structural distinction between institutions and individual members and employees. This distinction might circumvent the paralysing contrasts between more abstract human rights categories. This article approaches the question of conscience through the lens of a Dutch legislation on the position of wedding officials and in particular through a thorough critique of it by the Netherlands Council of State. The Council’s critique illuminates two important distinctions, first, between institutions and individuals and, second, between conscience and behaviour. These findings are potentially relevant in cases on access of lesbian, gay, and bisexual (LGB) people to services provided by private companies. For example, may photographers and videographers deny services to same-sex couples? May a bakery decline to supply wedding cakes? May a bakery refuse to create a custom-made cake for an LGB event? These questions arose, respectively, in the US cases Elane Photography, Telescope, and Masterpiece cases as well as the British Ashers Bakery case. And, should a Christian law school’s accreditation be rejected when a code of conduct impairs access of LGB students, eg in the Canadian Trinity Western cases?
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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 | 0.020 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.119 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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, 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".