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Record W7029918545

“‘Love all, trust few, do wrong to none. If only that were true… Is that why you keep us all so close?": Detective Inspector River’s inner victorian poisoner

2017· other· en· W7029918545 on OpenAlexaboutno aff

Bibliographic record

VenueePrints Soton (University of Southampton) · 2017
Typeother
Languageen
FieldArts and Humanities
TopicLibraries and Information Services
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretation (philosophy)DramaCriminal investigationRecklessnessCriticismDead body
DOInot available

Abstract

fetched live from OpenAlex

On Tuesday, 13 October 2015, BBC One broadcast the first of six one hour installments of the groundbreaking detective drama miniseries River, written by Abi Morgan. I refer to River as ‘groundbreaking’ not in reference to the critical reception and a review of its titular character DI John River (Stellan Skarsgård), but in appreciation of a drama that was saturated in a rich concept, was created in an impossibly intricate production process, involved the highest echelon of committed research and performance-centred talent, and offers inordinate academic possibilities in terms of critical interpretation. <br/><br/>For the purposes of this paper, interpretation will rest on the clear and present ways in which both the public and private aspects of our ‘anti-hero’, John River, pursues detection and rectifies criminality while practicing evasion in the detection of his disability. River offers a clear meta-narrative of crime, mental health drama; neo-gothic ghosting; psycho-social commentary; and Victorian true crime history on film while providing a collapsed survey of the detective, then and now, in a contemporary crime fiction that relies on a Victorian serial killer as foil. You see, John River is never alone on the beat or in his head because he hears voices. Voices of dead people. Oh…he sees and interacts with them as well. In public. Persistently. But only one goads him; only one angers him; only one does he fear, that of Thomas Cream (Eddie Marsan). <br/><br/>All of his Revenants are recent deaths that occurred on his watch, centrally that of his beloved partner DI Jackie “Stevie” Stevenson (Nicola Walker), who are with him for a time until they outlive their use. All except Cream – a true-life crime character from history. Thomas Neill Cream (1850 – 1892) was a Glaswegian-Canadian doctor, abortionist and serial killer who poisoned countless women internationally. Cream was arrested, following surveillance, for the murder of Matilda Clover in South London in July of 1892 and hung shortly there-after. River is reading a book on him at the start of the series, and he invades his consciousness in all the wrong ways. This paper critically interrogates the Cream and River relationship in the context of captivation, crime fiction, and psychic need. <br/>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.599
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0940.005

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.

Opus teacher head0.027
GPT teacher head0.209
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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