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Salvage Ethnography in the Financial Sector

2017· book· en· W2730182240 on OpenAlexaboutno aff
Jonathan Hearn

Bibliographic record

VenueManchester University Press eBooks · 2017
Typebook
Languageen
FieldSocial Sciences
TopicContemporary and Historical Greek Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyFinancial sectorFinancial crisisPath (computing)EconomicsFinancial systemBusinessFinanceSociologyKeynesian economicsAnthropologyComputer science

Abstract

fetched live from OpenAlex

This book takes ethnographic data collected in 2001-2, during a year’s fieldwork in the Bank of Scotland and HBOS, and revisits it from the perspective of the present, that is, after the global banking and financial crisis that emerged around 2008 with devastating effects on several banks, including this one. It focuses on the year in which Bank of Scotland merged with Halifax to form HBOS, scrutinising an encounter between two very different organisational cultures, embedded in Scottish and English national identities that are often symbolically opposed. Through this ethnographic setting it explores how bank staff coped with and made sense of rapid organisational change, and how those changes prefigured the crisis that was to come. That change was part of wider social and economic changes often associated with neoliberalism, heightened competition, and embattled social solidarity. Thus the study in a sense salvages a record of a disappearing banking culture, which is symptomatic of wider social change. The book contributes to our understanding of the stereotypes and mutual perceptions that shape Scottish and English national identities, while using the interpenetrating national and organisational contexts to critically examine the concept of culture. It also engages in an innovative way with the perennial problem of relating small-scale ethnographic data to large-scale historical change. Written clearly and concisely, with narrative momentum, it will appeal to students and scholars interested in the banking and economic crisis, national identity in Scotland and the UK, the nature of culture, and the challenges of ethnographic research.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0120.017
Scholarly communication0.0070.007
Open science0.0020.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.085
GPT teacher head0.259
Teacher spread0.175 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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