The Globalectics of Nationalism in CLR James’ and Michelle Cliff’s Writing
Bibliographic record
Abstract
Globalectics is the title and guiding principle of the Kenyan author Ngũgĩ’s recent collection of philosophical lectures on postcolonialism, globalization, and world literature, where he describes an engagement of the global environment through the local national landscape. The global roots of nationalism in the writing of Trinidadian and Jamaican authors such as CLR James and Michelle Cliff fit well with Ngũgĩ’s concept of globalectics. Ngũgĩ asserts, “The postcolonial is not simply located in the third world. Literally rooted in the intertextuality of products from all corners of the globe, its universalist tendency is inherent in its very relationship to historical colonialism and its globe for a theater” (Ngũgĩ 55). Global contexts greatly inform James’ and Cliff’s narratives of nationalist sentiment, as illustrated in James’ The Nobbie Stories for Children and Adults and Letters from London , and Cliff’s The Land of Look Behind and No Telephone to Heaven .
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".