Bibliographic record
Abstract
“Buddhism in Nova Scotia” describes the current Buddhist landscape in Halifax, Nova Scotia. The Buddhist ‘community’ in Nova Scotia is, not surprisingly, made up of distinct communities. This became apparent in 2003 when the Chaplaincy Office at Dalhousie University, in the interest of nurturing diversity on campus, tried to recruit a Buddhist Chaplain for the students. After a lengthy meeting, no agreement could be reached among the various groups on how to proceed with the chaplaincy appointment. The difficulty may be illustrated by the following example. Whereas the Shambhala Centre is managed by predominantly lay Euro-Canadians who offer free weekly hour-long Open House introductions to the Centre and a host of programs for young and old, Yunfeng of the Chan Temple, who speaks Putonghua, Cantonese and Vietnamese, is away from Halifax for at least nine months out of the year. When he was invited to speak to students in class at Dalhousie University, he declined and invited the students to visit the temple instead. He noted that his primary work was to practice and not to build a large sa?gha. This paper explores the diversity in the understanding of mission and its practical implementation in the Buddhist community of Dalhousie University and the city of Halifax.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.002 |
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".