Bibliographic record
Abstract
The influence of the Islamic culture on British literature has had its own tradition and representatives. By drawing on recent sociological, psychological and historical research about conversion to Islam in the West and on studies related to Sufi principles and aesthetics in literature, this paper explores and comments on some of the conditions which can nowadays lead to religious conversions, with a focus on the conversion from Christianity to Islam and on the poetic language of conversion. It argues that certain features of individual identity and an interest in therapeutic solutions to life’s problems can favour such once-in-a-lifetime decisions, as Paul Sutherland’s transcultural poetry exceptionally illustrates. David Westerlund (2004) writes that “Sufism has always been a multiplex phenomenon” (17), hence its universality and flexibility in its relationship with other cultures and religions. Born in Canada in 1947 in a family of British ancestry, Paul Sutherland arrived in the United Kingdom in 1973. The founder and editor of the international literary journal Dream Catcher from 1996 to 2012, he converted to Islam in 2004, when he became a follower of Shaykh Nazim Al-Haqqani and was given the name Abdul Wadud. He has published several poetry collections inspired by Sufi philosophy, such as Seven Earth Odes (2004), Spires and Minarets (2010), Journeying (2012), Poems on the Life of Prophet Muhammad (2014) or A Sufi Novice in Shaykh Effendi’s Realm (2014), fragments of which are briefly discussed below, in the light of a journey from Canadian Christianity to European type of Sufi Islam.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| 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".