Interfaith dialogue: Charity. A case for convergence in the Muslim and Christian faith traditions
Bibliographic record
Abstract
This dialogical thesis is about interfaith dialogue – primarily between the Muslim and Christian faith communities within the province of Nova Scotia, Canada. Christian and Muslim religions make up half of all the world religions. In Canada Christianity has been the predominate religion throughout its history. That demographic is beginning to shift, with Islam as the fastest growing faith in Canada, and Christianity continuing its decline in numbers since the end of WWII. Canada's culture is diverse and pluralistic, and heavily depends upon immigration to maintain its population growth and workforce. Canada has a strong record on Human Rights and embraces its rich diversity which makes it culturally distinct on the world stage. This creates a golden opportunity for Muslims and Christians in Canada to lead the way in effective interfaith dialogue. An understanding of the theologies and practices of charity in the Muslim and Christian faith traditions is a significant bridge that promises to lead to lasting peace, effective dialogue, and a joint working relationship with one another. If done properly, effective interfaith dialogue between the Christian and Muslim faith communities could potentially influence and change public policy for the alleviation of poverty within the broader communities they co-inhabit.
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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.055 | 0.078 |
| Scholarly communication | 0.025 | 0.016 |
| Open science | 0.003 | 0.030 |
| Research integrity | 0.008 | 0.014 |
| 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".