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Record W4206597168 · doi:10.46692/9781847421432.011

Challenging the disability benefit trap across the OECD

2005· other· en· W4206597168 on OpenAlexaboutno aff
Mark Pearson, Christopher Prinz

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsTrap (plumbing)PsychologyGeographyMeteorology

Abstract

fetched live from OpenAlex

Introduction Increasingly, disability benefits have become a trap for potential recipients who, once on benefit, typically stay there until retirement age. They are equally a trap for policy makers, who face – and, by and large, have failed to address – a choice between spending both political and financial capital in reforming what in nearly every country are patently seriously flawed policies, or ‘letting sleeping dogs lie’. Unfortunately, there appear to be few votes to be gained by reforming disability policies. Only when policy begins to collapse under the weight of its own contradictions do governments summon up the courage to introduce change. And these contradictions are legion: a policy designed for permanent disability having to cope with medical conditions which may be temporary; a benefit policy designed for those who cannot work yet in practice many or most recipients wish to work, and so on. This chapter briefly describes the magnitude of the dilemma across the Organisation for Economic Co-operation and Development (OECD), arguing that current policies are both expensive and yet fail to achieve satisfactory outcomes for people with disabilities themselves. It then discusses the primary causes driving current outcomes. Subsequently, it looks at disability policy trends in OECD countries since around the mid-1980s before turning to some very general policy conclusions. The chapter heavily relies on a 20-country comparative analysis published in early 2003 (OECD, 2003). The chapter concludes that no other area of social policy has been as ineffective in meeting the new challenges and in achieving its stated objectives as disability policy. The first problem: growing levels of benefit receipt At the turn of the 21st century, incapacity-related public cash spending across the OECD was as high as 2.3% of GDP, 2.6 times higher than unemployment-related spending (Figure 9.1). Only in Denmark was the latter higher than the former, and in Belgium, France and Canada cash spending on the two programmes was at the same level. In several countries, on the contrary, including the Czech Republic, Hungary, Iceland, Norway, Switzerland and the UK, incapacity-related cash spending was six to 12 times higher than unemployment-related cash spending. In the light of this, the strong focus of social policy and research on unemployment rather than disability issues seems unjustified.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.007
Science and technology studies0.0040.003
Scholarly communication0.0100.005
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0140.002

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 head0.167
GPT teacher head0.435
Teacher spread0.268 · 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 designObservational
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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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