Theorizing Literacies as Affective Flows: Attuning to the Otherwise Possibilities of Hip-Hop's “In-the-Red Frequencies”
Bibliographic record
Abstract
In this theoretical and conceptual article, we consider how meaning-making, literacies, identities, power, privilege, and in/equities are entangled with/in non/human sociomaterial force relations. Inspired by Rose, we build theoretically on the philosophical principles of hip-hop—flow, rupture, layering, and sampling. Conceptually, we invite literacy educators to attune to “in-the-red frequencies,” or “noisy” political philosophies and practices that Black people have used to create alternative realities to white supremacist patriarchal systems of oppression. Afrodiasporic approaches to mobility and sounding pivot us away from humanist ways of knowing/being/doing/researching literacy and toward more creative, emergent, and “fugitive modes.” Ultimately, we argue that theorizing affective literacies via flow↔rupture↔layering↔sampling enables ethical teaching, learning, and research practices that respect multiple perspectives, histories, and truths; account for affect, power, privilege, positioning, and complicity; and highlight “otherwise worlds” not predicated on hegemonic whiteness, anti-Blackness, and sociopolitical violence.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.038 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".