Multi Consciousness: Simultaneity, Splintering, and Structures of Feeling in Contemporary American Fictions of Displacement
Bibliographic record
Abstract
Multi consciousness is a cross-cultural and cross-temporal affective structure which poses questions regarding how different modes of displacement (enforced relocation, immigration), erasure (social and political), and violence affect formations of consciousness, and how representations of subjecthood or lack thereof alter perceptions of self. I unpack the metaphor of the multiplied, fragmented and split as it is repurposed in contemporary American fictional works of displacement to understand how multiplicity resonates more destructively with displaced and marginalized individuals. Multi consciousness accounts for and contains double, triple, and mestiza consciousness, and furthermore articulates the complexities of marginalized subjecthood in the contemporary moment—in the moment of ever-present technology where everything is instantaneous and multiplied, in the moment continued and ongoing racial and identity politics. \nI will discuss multi consciousness as a shared structure of feeling, as a practice of assimilation and mourning, and the various metaphors of multi consciousness that contemporary American fictional works of displacement engage in. The dissertation works through Toni Morrison’s The Bluest Eye (1970), Danzy Senna’s Caucasia (1998), and Brit Bennett’s The Vanishing Half (2020), Eric Nguyen’s Things We Lost to the Water (2021), Charles Yu’s Interior Chinatown (2020), Viet Thanh Nguyen’s The Sympathizer (2015), James Welch’s Winter in the Blood (1974), Leslie Marmon Silko’s Ceremony (1977), Tommy Orange’s There There (2018), Ted Chiang’s “Story of Your Life” (1998), Arrival (2016), and Everything, Everywhere, All at Once (2021). I look to these works to outline the condition of multi consciousness: mourning, the sense of being haunted, displacement and diaspora, multiple competing ways of inhabiting the body/being in the world, the sense of inhabiting multiple timelines/worlds, the presence of whiteness as consciousness, seeking/creating a double of the self, and disassociation. Through this varied bibliography, I argue that multi consciousness surfaces as an evident cross-cultural, cross-generational, shared structure of feeling within contemporary American fictions of displacement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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".