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Record W1550728581

Power and Welfare: Understanding Citizens' Encounters with State Welfare

2012· book· en· W1550728581 on OpenAlexaboutno aff
Nanna Mik‐Meyer, Kaspar Villadsen

Bibliographic record

VenueCBS Research Portal (Copenhagen Business School) · 2012
Typebook
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWelfareWelfare statePower (physics)State (computer science)Political sciencePublic economicsEconomicsComputer scienceLawPoliticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

In the welfare provision of today, power takes both the shape of juridical sanctions and of attractive offers for self-development. When state institutions punish criminals, remove children at risk, or enforce sanctions upon welfare recipients the question of power is immediately urgent. It is less readily evident that power is at stake when institutions educate, counsel or 'empower' citizens. This book offers a framework for understanding and analyzing these complex and implicit forms of power at play in the encounters between citizens and welfare institutions. Taking as its starting point the idea that power takes many different shapes, and that different approaches to power may be necessary in the diverse contexts where citizens encounter welfare professionals, the book demonstrates how significant social theorists, spanning from Goffman to Foucault, can be used for inquiries into these encounters. Guiding the reader from their epistemological foundations to lucid 'state of the art' case examples, the book unpacks each of its six theoretical perspectives, and explains selected key concepts and explicates their potential for analysis. The final chapter discusses the usefulness of the theoretical approaches, their weaknesses and indicates some possibilities of theoretical integration. Including case studies of patients, nursing home residents, unemployed people, homeless people, and young offenders, from the USA, Denmark, France, Sweden, Canada, and Australia, Power and Welfare is designed for students and researchers of social policy, sociology, anthropology, political science, education, nursing and social work.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.091
GPT teacher head0.365
Teacher spread0.275 · 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

Citations51
Published2012
Admission routes1
Has abstractyes

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