Bibliographic record
Abstract
"In this special issue, we attempt to take a fresh look at the nature and authority of conscience, and to consider the extent to which the law should recognize claims of conscience. Most of the papers included here developed from drafts presented at the IVR World Congress in Bucharest, Romania in 2022. Other papers were solicited from qualified individuals unable to attend that event in person. The contributions have been curated into three main sections, moving from more general philosophical questions, to fundamental jurisprudential concerns, and then to specific dilemmas of conscience we face today. On paper, the 1982 Canadian Charter of Rights and Freedoms provides expansive, constitutional protections for freedom of conscience. Yet, as Janet Epp Buckingham argues, when put to the test, courts have typically permitted major infringements of rights of conscience. Legal challenges based on conscientious objections to blood transfusions, military service, solemnizing same-sex marriages, and participating in activities sanctioned by MAID laws have routinely been struck down by courts, and this calls into question the practical significance of the Charter. The Charter is an impressive legal achievement, but more work needs to be done to make a reality of its admirable aim to protect rights of conscience and fundamental liberties."--
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
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".