Bibliographic record
Abstract
The concept of racial ambiguity, or the quality of challenging existing racial categories, helps us understand Aleksandr Pushkin, a Russian poet of partially African descent famously known as “protean.” According to memoirs about the poet, in his own lifetime Pushkin’s African heritage did not prevent him from being categorized as Russian, but it distinguished him from his peers. Moreover, as a light-skinned mixed-race individual, Pushkin challenged reigning notions of Africanness. Pushkin did not fit perfectly into the categories of either “Russian” or “African.” This ambiguity is reflected both in memoirs about the poet and in Pushkin’s story “The Lady Peasant” (1831), whose heroine adopts different identities over the course of the text. While she crosses class rather than racial boundaries, the story’s broader, intertextual context and Pushkin’s focus on her dark skin suggest that race informs her performance. This paper thus suggests that we can better understand the writer’s treatment of shifting identities when we think of Pushkin not just as racially marked (as African or Black) but as racially ambiguous.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".