Working futures?Disabled people, policy and social inclusion
Bibliographic record
Abstract
Part 1: Work, welfare and social inclusion: challenges, concepts and questions: Working futures: critical debates in disability employment policy ~ Alan Roulstone The missing million: the challenges of employing more disable people ~ Kate Stanley Part 2: The current policy environment: New deal for disable people: what is new about New Deal? ~ Bruce Stafford Work preparation: a preparation for a real job or part of the revolving door? ~ Sheila Riddell and Pauline Banks Legislating for equality: evaluating the Disability Discrimination Act 1995 ~ Nigel Meager and jennifer Hurtsfield Disability frameworks and monitoring disability in local authorities: a challenge for the proposed Draft Disability Bill ~ Ardha Danieli and Carol Woodhams Job retention: a new policy for disabled people ~ Geof Mercer Benefits and tax credits: enabling systems or constraints? ~ Anne Corden Challenging the disability benefit trap across the OECD ~ Mark Pearson and Christopher Prinz Jobcentre Plus: can specialised personal advisors be justified? ~ Patricia Thornton Disability and employment: global and national influences in New Zealand, Canada and Australia ~ Neil Lunt Disabled people and 'employment' in the majority world: policies and realities ~ Peter Coleridge Part 3: Towards inclusive policy futures: Employment policy and practice: a perspective from the Disabled Peoples' Movement ~ David Gibbs The relevance of the social model of disability for the work aspirations of people with enduring mental health problems ~ Jennifer Secker and Bob Grove Enabling futures for people with learning difficulties: exploring the employment realities behind the policy rhetoric? ~ Danny Goodley and Ghashem Nourouzi Barriers to labour market participation: the experience of Deaf and hard of hearing people ~ Jennifer Harris and Patricia Thornton Work matters: visual impairment, disabling barriers and employment options ~ Phillipa Simkiss Disabled people and employment: the potential impact of European policy ~ Hannah Morgan Missing pieces: the voluntary sectors' potential for inclusive employment ~ Lorraine Gradwell Professional barriers and facilitators: policy issues for an enabled salariat ~ Bob Sapey and Jeannine Hughes Disabled people, the State and employment: historical lessons and welfare policy ~ Jonathan Warren Work is a four letter word: disability, work and welfare ~ Colin Barnes and Alan Roulstone Conclusions.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.022 | 0.063 |
| Scholarly communication | 0.032 | 0.039 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.032 | 0.023 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".