SPEP Co-Director's Address: Hesitation as Philosophical Method—Travel Bans, Colonial Durations, and the Affective Weight of the Past
Bibliographic record
Abstract
ABSTRACT The 2017 “travel bans”—curtailing travel into the United States for nationals of several Muslim-majority countries—make palpable the skewed possibility of movement that comes with belonging to a nationality or passport. My experience of navigating travel as an Iraqi-Canadian gives rise to a critical phenomenological reflection on the affective weight of colonial pasts. The colonial past remains with the present; it is intensified through repeated enactment in U.S. policy but also through the weight of its duration and indifference toward it. It is differentially remembered, cognized, and felt—disregarded from white and U.S.-centric perspectives, yet palpably structuring the everyday for the occupied, racialized, and “formerly colonized.” Sometimes it is felt in the form of hesitation. I ask how hesitation can become critical and what its role might be in redressing the past. My theory of time—Bergsonian yet moving beyond Bergson—helps me think this question. I argue that the past coexists with the present and is reconfigured along with it, in a process I liken to kneading or folding dough. While the past's colonizing fractures cannot be healed, they can be felt, made perceptible, and thought—in attentive reconfiguration of the past, worked through in a critical phenomenology.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".