London as a Safe Haven? Asylum, Immigration and Missing Fingers in Chris Cleave’s The Other Hand (2008) and Brian Chikwava’s Harare North (2009)
Bibliographic record
Abstract
The years 2008 and 2009 saw the publication of, respectively, Chris Cleave’s The Other Hand (published in the US and Canada under the alternative title Little Bee ) and Brian Chikwava’s Harare North , two celebrated novels that take young asylum seekers of African origin living in London as narrator-protagonists. Each received a good deal of critical praise. While sales of The Other Hand were initially slow — the novel had no advertising and very little marketing, and sold around three thousand copies in 2008 — its sales increased dramatically over time and, as of February 2014, has sold more than half a million copies in the UK alone. 1 It has also proven popular in the United States; in March 2010, it spent three weeks at the top of the New York Times Best Seller list for paperback fiction. 2 It was short-listed for both the 2008 Costa Novel Award and the 2009 Commonwealth Writers’ Prize, and a number of companies expressed interest in making a screen adaptation of the novel and made offers accordingly; BBC Films eventually acquired the rights and an adaptation may yet surface. In contrast, while Harare North was critically acclaimed and was long-listed for the George Orwell Book Prize 2010, as of February 2014 it has sold just two thousand copies in the UK. 3 Chikwava’s debut novel deserves to sell a great many more copies. 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.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".