Bibliographic record
Abstract
During the completion of this book I lived, worked, and breathed in Katarokwi (Kingston) and Tkaronto (Toronto).I continue to learn about the traditions, ancestors, and keepers of these lands, especially of the Haudenosaunee and Anishinaabek peoples.As a settler of colour, I recognize that my presence here furthers the displacement of Indigenous peoples who have been and are the protectors of these lands, waters, air, and creatures.As someone who was displaced from the civil war in Sri Lanka, the irony of my presence on Turtle Island is not lost on me: the costs of colonialism, imperialism, and nationalism continue to result in settler-colonial violence and displacement on Turtle Island and around the globe.My solidarity remains with Indigenous communities and their sovereignty, and with all communities suffering oppression and occupation.The opening for this book would not have been possible without my friend Shams al Haqq Farzad AttarJafari.Farzad and I connected over a decade ago, and even though we have tried collectively to dig through our memories we still can't figure out when our first meeting was.I do remember seeing him turn for the first time in 2009, when I was taken to my first sama at the Jerrahi Order in Toronto.I could not have imagined then that this book would be part of my future.Since then, he has become a dear friend and teacher to me, and has even come to spend time with my students, be it in Ithaca, New York, or Kingston, Ontario.He has also welcomed me to collaborate with him on his projects.When I first mentioned this book idea to him and I asked for help getting in touch with Sufis and samazens, especially in Vancouver, he did not miss a beat.If it was not for his phone calls and WhatsApp messages, I would not have been able to connect with most of the dervishes in this book.Farzad (Shams), my deepest gratitude and love to you, Ya Hu!With the help of Farzad, I connected with John Brozak, who has been gracious with his time, his insights, and his personal archives.John replied to all my questions and detailed queries via emails and texts, welcomed me to
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.401 | 0.244 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".