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Community in contemporary British fiction from Blair to Brexit

2022· book· en· W6910618020 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Repository (Kingston University London) · 2022
Typebook
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBrexitReading (process)Representation (politics)Relation (database)Focus (optics)Task (project management)

Abstract

fetched live from OpenAlex

"Examining how British writers are addressing the urgent matter of how we form and express group belonging in the 21st century, this book brings together a range of international scholars to explore the ongoing crises, developments and possibilities inherent in the task of representing community in the present. Including an extended critical introduction that positions the individual chapters in relation to broader conceptual questions, chapters combine close reading and engagement with the latest theories and concepts to engage with the complex regionalities of the United Kingdom, with representation of writers from all parts of the UK including Northern Ireland. Including specific focus on the most challenging issues for community in the past five years, notably Brexit and the Covid-19 crisis, with a broader understanding of themes of local and national belonging, this book offers detailed discussions of writers including Ali Smith, Niall Griffiths, John McGregor, Max Porter, Amanda Craig, Bernadine Evaristo, Jonathan Coe, Bernie McGill, Jan Carson, Guy Gunaratne, Anthony Cartright, Barney Farmer, Maggie Gee and Sarah Hall. Demonstrating some of the resources that literature can offer for a renewed understanding of community, this book is essential reading for anyone interested in how British Literature contributes to our understanding of society in both the past and present, and how such understanding can potentially help us to shape the future."

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.488
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.073
GPT teacher head0.319
Teacher spread0.246 · 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; a candidate call from one teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

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