Bibliographic record
Abstract
Despite the interdisciplinary focus on what Edward Soja has coined the ‘spatial turn,’ there has not yet been an extended investigation into literary representations of contemporary British urban spaces forever changed by shifts in Margaret Thatcher’s sociopolitical policies of privatization during the 1980s and beyond.1 Working through cultural theories set forth by Stuart Hall at the intersection of urban, geographic, and literary studies, the present study builds on Soja’s concept of a ‘critical spatial perspective’ of urban spaces, since, as he suggests, the ‘social is always at the same time … spatial’ (8). It is with this ‘spatial turn’ in mind, specifically ‘the reassertion of a critical spatial perspective in contemporary social theory and analysis’ (Soja 1), that I undertake my examination of literary representations of British urban spaces under and after Thatcher. Identifying the crossroads of politics, culture, and shifts in capitalism, I turn to the dialectic linkages between space, identity, and capitalism (Smith, Harvey) in order to discuss textual representations of the struggles of class, race, and identity in Thatcher’s Britain. With the ‘spatial turn’ as my theoretical foundation, this book examines literary representations of the sociocultural and political effects of Thatcherite social programmes and policies of privatization as they considerably altered the connection Britons had with urban processes, citizenship, and the spatiality of the city.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.498 | 0.320 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".