Bibliographic record
Abstract
The experience of exile greatly impacted on Edward Said’s intellectual, literary and political writings. Exile, Said writes, creates a terrible rift between one’s self, people, land, language and culture. This paper investigates the condition of exile and how it frames Said’s shifting ideas of humanism in a postcolonial world. I argue that Said’s readings of humanism and faith in the humanities can serve as a forum for understanding the incomprehensible situations of world conflict. This paper considers concepts critical to Said’s concepts of postcolonial humanism that we cannot afford to dispense with but must rethink to redress the situation of exile that is the cause of so much unrest in the world today. Postcolonial humanism attests to the particularity and diversity of human experience across a range of shared and unthinkable histories, which bears witness to and reminds us of a shared humanity. With Said, I will argue for a postcolonial humanism without need of identity, nation or property and for the renewal of principles of sustainable exiled existence that we can live with. Despite the politicised grievances we unevenly hold against a world turning against us, there is still something important to learn from our shared postcolonial condition. Said’s writings on exile, I suggest, have relevance for those committed to the engagement of ideas and understanding in a world increasingly marked by mass violence, ecological devastation and destruction.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.034 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| 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".