Religious Reasons and Public Reason: Recalibrating Ireland’s Benevolent Secularism
Bibliographic record
Abstract
Liberal regimes in the West are not homogeneous in their application of secular principles. What kind of “secular” state a particular government promotes depends in large part on the strength and influence of the majority religion in that region. This article acknowledges the heuristic value of a recent threefold taxonomy of secularism: passive, assertive, and benevolent forms of secularism. I take issue with and challenge certain institutional privileges granted to the majority religion in one benevolently secular regime, the Republic of Ireland. I consider how benevolent secularism, while remaining benevolent toward religion, can align its application of secularism in the arena of publicly-funded education (primary and secondary education). A politically liberal regime, defined by the idea of public reason, invokes the principle of publicity, namely, that discourse and public policy be intelligible (and acceptable to a large degree) not only to an individual’s religious or moral community but also to the broader collection of members who constitute a liberal state. Drawing on John Rawls’ conception of public reason, and using Ireland as a case study, I show how this particular state-religion interrelation can be recalibrated in order to increase the prospects of reconciliation with a secular space of public reason.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.020 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".