Not a place, but a culture: the cultivation of Iranian subjectivity in Montreal
Bibliographic record
Abstract
This thesis analyzes how a network of Iranian artists and intellectuals, living in Montreal, cultivate a particular subjectivity by engaging in cultural practices such as weekly cultural gatherings which generally focus on literary, artistic, historical and/or philosophical discussions. In order to study this process I conducted an ethnographic study from June 2008- May 2009 primarily concerned with gathering qualitative research. The ethnography specifically focuses on two Iranian artists and a group called CaféLitt. It is through this cultural practices or practices of association that Iranians in Montreal engage with one another and certain discourses, such as Persian poetry and Iranian history, to cultivate/perform a particular sense of self. This thesis also presents space as an essential category of study and considers, by using a multi-dimensional definition of space borrowed from David Harvey, how the spaces Iranians in Montreal frequent - whether they be Iranian businesses, art galleries, cafes, etc - take an active role in the process of their subject formation. The self Iranians in Montreal cultivate is one that continues to be Iranian because of a repeated citation of key discourses that make Iranian culture, but this self is also transformed by the new space the immigrants exist in and by one of the goals of CaféLitt which is to practice certain ideas of liberal culture, including self-improvement through education.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".