(A)Drift: A Method and Theory of Black Temporality in <i>Map</i>
Bibliographic record
Abstract
Taking seriously Brand’s conception that we “have no such immediate sense of belonging, only of drift” ( Brand 2001 , 118), this commentary meditates on Brand’s conception of “drift” as both a theory and method of Black temporality. Dionne Brand’s A Map to the Door of No Return: Notes to Belonging (2001) draws us towards the uncharted/able expanse of the Door of No Return, and particularly the ways the Door overwhelms temporal senses and experiences. The Door, Brand describes, is a passport from a territory so vast that “[w]e are always in the middle of the journey” ( Brand 2001 , 49). Map invites us not only to consider the inadequacies of origins and nation-state boundaries. Map also theorizes the inability of normative temporal schemas to render sensible the “past’s” ongoing presence in Black life in the wake(s) of the Door and the Middle Passage of racial slavery. Mirroring Brand’s weaving of personal narrative and theory, this reflection turns to the relationship between forgetting and time, particularly in intergenerational conversations, to understand how the Door disorients normative logics of time as a dimension of Black psychic life that people share in. In doing so, this reflection sits with how Map names a temporality of the Door that is not about fantastical change or transformation, but about continuous arrivals to the experience of a suspension that one never quite leaves.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".