Bibliographic record
Abstract
In the deft deconstructive move with which she ends Borrowed Tongues, Eva Karpinski invokes Jacques Derrida’s reflections on monolingualism to conclude, “language belongs exclusively to no master; no dominant culture” (227). According to Karpinski, the various women whose life writing she examines challenge the concept of speaking and writing “in ‘borrowed tongues’ since no property rights can be asserted over any language” (227–28; my emphasis). By testing the trope of borrowing, however, Karpinski by no means undermines the analyses that make up this unique study. Rather, she highlights exploitative assumptions about dominant languages that underpin a world increasingly characterized by migrancy and displacement, and confronts powerfully the notion that the English language is “‘owned’ and can be used as a legitimate instrument of exclusion” (228). Karpinski uses the metaphor of borrowed tongues in several ways, to refer first to writing “literally in a second language or a language which is perceived as not one’s own,” a language that migrants, immigrants, and other displaced subjects have “on loan” from a dominant culture. However, indigenous and postcolonial subjects also borrow tongues when they use the language of colonial oppression to challenge cultural imperialism and the dominance of Standard English. To these two, Karpinski adds a third, more sinister meaning of borrowing, linked to economic dependence in the context of global neoliberalism, and, finally, she deploys the metaphor to describe any discursive activity that engages with “dominant ideologies of gender, class, and racialization, the imposition of normative (hetero)sexuality, and the hegemonic constructions of religion, ethnicity, and citizenship” (2).
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
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".