Bibliographic record
Abstract
The year 2002 marked a pivotal moment in the American Catholic Church when a scandal erupted in Boston, unveiling a systemic crisis of clerical sexual abuse. This event unleashed a tidal wave of revelations that rippled through the Church, shattering the prevailing facade of "business as usual" and exposing a hidden stream of abuse that had flowed beneath the surface for decades. This paper examines the profound impact of the Boston scandal on the Catholic Church, both in the United States and in Europe. This study delves into four reports from Europe and the United States, shedding light on the extent of the issue in each region. It aims to bridge a gap in the literature by providing a comprehensive analysis of these reports, emphasizing that the problem is not exclusive to the Church but is a societal issue. The examined reports reveal varying rates of abuse and abusers across countries, highlighting the need for a broader societal approach to combat child abuse. This research underscores the importance of confronting the issue transparently and acknowledges the critical role played by independent investigations, such as the John Jay Report. The data from these reports are essential in dispelling misconceptions and fostering a fact-based understanding of clerical abuse. In conclusion, this comparative analysis examines key findings from reports in the United States, France, Germany, and Ireland, highlighting both similarities and differences.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".