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Record W655927734

Leadership and change in human services : selected readings from Wolf Wolfensberger ; compiled and edited by David G. Race

2003· book· en· W655927734 on OpenAlexaboutno aff
Wolf Wolfensberger

Bibliographic record

VenueRoutledge eBooks · 2003
Typebook
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsSuccessor cardinalHuman servicesContext (archaeology)Gray (unit)Race (biology)Normalization (sociology)Political scienceRelevance (law)SociologyEnvironmental ethicsManagementSocial scienceHistoryGender studiesLawMedicine
DOInot available

Abstract

fetched live from OpenAlex

For over forty years Wolf Wolfensberger has been a significant figure in the world of human services, especially in the field of learning disability. His work on normalization and citizen advocacy in the late 1960s and early 1970s has been acknowledged by supporters and critics alike to have been fundamental to developments in a number of countries, most notably his adopted country, and the USA, Canada, Australasia, and the UK. His further work in developing the theory of social role valorization, the successor to normalisation, and as a commentator on broader trends in society and their effects on vulnerable people and services for them has ensured his place as a major voice for values and the human worth of all people. Never afraid of controversy, his views have brought him into conflict with institutional vested interests and radical groups alike. In Leadership and Change in Human Services David Race introduces the reader to Wolfensberger's key ideas through a series of extracts, with commentary, from his published work. Throughout the edited selection, the emphasis is on placing Wolfensburger's work in contemporary context and examining its continuing relevance today. Including a comprehensive bibliography of Wolfensburger's written output, this text offers an invaluable source of reference to all those concerned with the recent history of the human services.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.085
GPT teacher head0.329
Teacher spread0.244 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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