Bibliographic record
Abstract
In contrast to Britain, whose visibly imperialist mission led it to colonize much of the world in the nineteenth century, the United States has concealed its imperialism and positioned itself beside the postcolonial “settler colonies” dominated by imperial powers. Public myths of American origins and identity ring with assertions of individual liberty and the rights of the common man, asserted against the oppressions of imperial Britain. Amy Kaplan writes that “Most current studies of imperial and postcolonial culture […] tend to omit discussions of the United States as an imperial power,” in part because nationalist discourse has insistently defined the nation as “inherently anti-imperialist” (1993: 17, 12). Even postcolonial scholars looking at US imperialism can miss it, as do Ashcroft, Griffiths, and Tiffin in their influential book, The Empire Writes Back . Listing postcolonial literatures, they include the United States with Canada, Australia, and others as rejecting imperial assumptions: “The literatures of the USA should also be placed in this category. Perhaps because of its current position of power, and the neo-colonizing role it has played, its post-colonial nature has not been generally recognized. But its relationship with the metropolitan centre as it evolved over the last two centuries has been paradigmatic for post-colonial literatures everywhere” (2). 1 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".