Bibliographic record
Abstract
Courts around the world require witnesses to swear an oath to a religious deity or affirm to tell the truth before providing testimony. It is widely thought that such a process has the potential to give rise to unnecessary bias against witnesses based on their religious beliefs or lack thereof. Scholars have offered two main prescriptions to remedy this problem: (i) abolish the oath and have all witnesses promise to tell the truth; or (ii) require oath-swearing witnesses to invoke a non-specific reference to God. The former proposal is problematic as it rests on the unproven assertion that giving an oath does not bind at least some witnesses’ conscience to a greater extent. The latter fails to protect against bias towards atheists and other witnesses who refuse to swear an oath. The aim of this article is to develop an alternative procedure that allows witnesses to swear an oath or affirmation outside of the courtroom. This process not only rids the trial process of unnecessary bias, it also furthers the truth-seeking function of the trial process by allowing witnesses to bind their consciousness to a greater extent.\nLes tribunaux du monde entier exigent des témoins qu’ils prêtent serment à une divinité religieuse ou qu’ils affirment solennellement de dire la vérité avant de témoigner. Il est largement admis qu’un tel processus peut donner lieu à des préjugés inutiles à l’encontre de certains témoins en raison de leurs croyances religieuses ou de l’absence de celles- ci. Des chercheurs ont proposé deux solutions principales pour remédier à ce problème : (i) abolir le serment et faire en sorte que tous les témoins promettent solennellement de dire la vérité; ou (ii) exiger que les témoins qui prêtent serment invoquent une référence non spécifique à Dieu. La première proposition est problématique car elle repose sur l’affirmation non prouvée que le fait de prêter serment ne lie pas davantage la conscience d’au moins certains témoins. La seconde proposition ne protège pas contre les préjugés à l’égard des personnes athées et des autres témoins qui refusent de prêter serment. L’objectif du présent article est d’élaborer une procédure de rechange qui permettrait aux témoins de prêter serment ou de faire une affirmation solennelle en dehors de la salle d’audience. Cette procédure permettrait non seulement d’éviter toute partialité inutile, mais elle renforcerait également la fonction de recherche de la vérité du procès en permettant aux témoins de lier leur conscience dans une plus large mesure.
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 | 0.094 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.008 | 0.021 |
| Insufficient payload (model declined to judge) | 0.015 | 0.009 |
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".