Bibliographic record
Abstract
This book takes a body of ethnographic data collected in 2001-2, during a year's fieldwork at the Bank of Scotland (BoS) and HBOS, and revisits it from the perspective of the 2014-16 period. It explores the tension between the 'ethnographic present' of the author's original research and the unavoidable alteration of perspective on that data that the economic crisis has created. The original research had been planned to take place in the BoS but in 2001, before the research began, BoS had merged with the Halifax to form HBOS. The book provides a long-term historical perspective on BoS/HBOS, from inception to the 2008 financial crisis, and then a consideration of the nature of historical explanation, under the rubric of 'theory'. The main attempts to explain the proximate causes of the 2008 crisis, as well as more encompassing political economic arguments about the trajectory and dynamics of capitalism are examined. The concept of 'culture' as applied to both national groups, Scots and English, and organizations, BoS and Halifax, are also dealt with. The book examines other governing concepts such as organisational change in the business world and social change, identity and the way Scottish and English experience their own personhood, and comparative nature of ethnographic research. The conclusion reviews and draws together the themes of the book, returning to the overarching question of historical perspective and explanation.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".