Dickens and Demolition by Joanna Hofer-Robinson, and: Dickens and the Stenographic Mind by Hugo Bowles
Bibliographic record
Abstract
One of the first questions to ask of any new Dickens studies monograph is: How does it situate the Inimitable himself?How is Dickens's life and celebrity placed in relation to his works and their contexts, and what impact does that have upon the conclusions the work reaches as a result?In two rigorously researched new studies, Dickens and Demolition and Dickens and the Stenographic Mind, Joanna Hofer-Robinson and Hugo Bowles take very different approaches to Dickens as author.Bowles's study focusses primarily on production and inspiration, tracing Dickens's journey to stenographic literacy and considering how that literacy imprinted itself upon his fiction throughout his career.In this way, Bowles places Dickens's mindset and intentions centre stage, suggesting that a proficiency in shorthand enabled him to manipulate language in ways unavailable to other authors and to control how readers engaged with his novels.In contrast, Hofer-Robinson's study focusses on contexts of reception and remediation.Building upon recent work on literary afterlives, such as Casie LeGette's Remaking Romanticism: The Radical Politics of the Excerpt (2017) and Mary Hammond's Charles Dickens's Great Expectations: A Cultural Life (2015), Hofer-Robinson shows how Dickens's fictions were variously used to facilitate discussions about urban improvements and demolition projects in London.She persuasively concludes that the strategic deployment of the fictional world can have a material impact.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".