<特集 ヴァナキュラー・ツーリズムからみる南アジア --宗教・聖地・観光-- > The Times of India 紙デジタルコレクションが記録したスィク教徒の旅 --パキスタン・イスラーム共和国におけるグルドワーラー巡礼--
Bibliographic record
Abstract
Pakistan issues pilgrimage visas to Indian Sikhs in compliance with the ‘1974 Protocol on Visits to Religious Institutions.’ In 2018, the Pakistan High Commission Office in New Delhi issued 3, 800 visas to Indian Sikhs. Indian pilgrims enter Pakistan through the Wagah border by rail or road and undertake pilgrimage to several sites. Large groups are organised, especially on the death anniversaries of gurus, the Vaisakhi (harvest festival) in April and the Guru Nanak Jayanti festival in November. For a few days every year in November, thousands of Sikhs gather at the city of Nankana Sahib in Pakistan to celebrate Guru Nanak Gurpurab -- the birth anniversary of Guru Nanak, the founder of Sikhism. They arrive from India, the Middle East, the UK, Europe, Canada, the US, and all over the world. It is one of the biggest pilgrimages in the Islamic Republic of Pakistan. In this paper, focussing on the Sikh community, I clarified the historical situation of minority pilgrimages that has received very little attention in Pakistan and explored the social significance of these pilgrimages. An attempt was made to locate relevant articles from archives of The Times of India, an Indian newspaper, to reconstruct the historical narrative.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".