Civil or Religious Paths to Respect and Understanding? Two Commonwealth Reports
Bibliographic record
Abstract
While trends towards secularization may have appeared inexorable as the last century came to a close, more recent events, particularly in the aftermath of 9/11, have led to greater attention being paid to the resurgence of religion globally.But how to represent and portray religion, with respect and understanding, in this new environment may contain significant challenge-a subject which this paper considers in the light of two recent Commonwealth Reports.The Report of the Commonwealth Commission on Respect and Understanding, entitled Civil Paths to Peace, chaired by Amartya Sen, and presented recently to the Commonwealth Heads of Government summit in Kampala, Uganda, seeks to downplay any single-minded concentration on religion in favour of promoting broader civil engagements in crafting civil paths to peace.In contrast, the Commonwealth Foundation's Report, Engaging with Faith, treats religion more sympathetically and encourages understanding and cooperation between the faith communities.The former Report may tend to treat religion as part of the problem, while the latter might view religion as part of the solution.Thus, the two Reports illustrate contrasting and conflicting views as to the place of religion in efforts to promote global peace and development along the path to respect and understanding.
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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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".