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Record W4312041698 · doi:10.51952/9781447353713.ch002

A hand up, not a handout

2022· book-chapter· en· W4312041698 on OpenAlexaboutno aff
Emma Mitchell

Bibliographic record

VenuePolicy Press eBooks · 2022
Typebook-chapter
Languageen
FieldHealth Professions
TopicHealth Services Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Chapter 2 provides the big picture backdrop for the rest of the book by placing Australia’s welfare system in international and historical context. It gives an overview of the resurgence and rise of more meagre and punitive welfare in Australia and the targeting of sanctions and supports at the most vulnerable welfare users with ‘complex needs’. While moral distinctions between the ‘deserving’ and ‘undeserving’ poor have returned to prominence over the last three decades, they are deeply rooted in the foundations of the Australian welfare state. The chapter briefly outlines the history of exclusions and ‘conditional inclusion’ embedded in welfare provision, and how the settler-colonial welfare state dealt with Indigenous and non-white immigrant difference. The chapter concludes by situating Australian developments in relation to similar shifts in the UK, Aotearoa/New Zealand and Canada.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.078
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0060.010
Open science0.0010.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0780.044

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 head0.211
GPT teacher head0.455
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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