Bibliographic record
Abstract
Over three decades, Justin D. Edwards investigated a diverse range of subjects within the Gothic, from tropes of racial passing in American Gothic to postcolonial Gothic literature to Canadian Gothic literature and beyond. What united Edwards’s array of interests was a consistent concern for justice, both in terms of socioeconomics and in terms of climate change. In keeping with this overall emphasis, and expanding it beyond literary studies, this article will explore the ‘The Deep’ by Clipping, a song which connects the historical dehumanization and consequent horror of the Atlantic Slave trade to contemporary environmental abuses and socioeconomic injustice. The song notably builds upon and revises HP Lovecraft’s Ancient Ones as the return of the monstrous repressed. Instead, the ‘ancient ones’ are the ones deemed excess, cast overboard like so much extra cargo by previous generations. Clipping’s Ancient Ones furthermore rise to enact a much-needed revolution in response to humanity’s environmental crimes. Those that rise from the deep are thus reminders of humanity’s failure to change and a mark of inevitable destruction and horror that awaits if we continue to refuse to change. The song thus merges the Gothic with Afrofuturism in ways difficult to contain within a single category, as the song is not Afropessimist but certainly induces panic in its methods even as it rewrites previous Gothic and weird texts in articulating its vision for an inevitable, post-human future.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".