Introduction: the challenge of a living wage
Bibliographic record
Abstract
This book addresses one important way of dealing with minimum claims to justice through decent minimum or living wages. These claims have come at a time when widening inequalities have become an unavoidable fact (Nolan and Valenzuela 2019), one made worse by the COVID-19 pandemic and economic crisis that started in 2020. Even before then, the steady flow of reports documenting rising inequality in the rich ‘liberal’ world, coming from reputable and technically minded agencies, was not surprising, given that a decades-long push to return to ‘business rule’ in the economy and the labour market was designed to expand the profit share. As French social scientist Thomas Piketty (2013) has persuasively shown in his Capital in the Twenty-First Century , the concentration of wealth and its tendency to produce higher returns than the general growth rate mean that the present century risks seeing rising income and wealth inequality, a problem only reversed after World War Two with massive government intervention (see also Cassidy 2014). The countries that form the particular focus of this book are the six English-speaking ‘liberal’ welfare states of Australia, Canada, Ireland, New Zealand, the United Kingdom, and the United States. They form a distinct cluster in analyses of welfare states and work relations, and although there are important differences between these countries and their politics and policies, they have followed policies antithetical to the remedies for runaway inequality that Piketty has identified. The consequences have been widening inequality, particularly in the UK and the US (Piketty 2013, Figure 9.2). These two countries have been completely transformed by rising inequality. High and rising inequality causes social and political malaise, evident in crime, mistrust, unhealthy individualism, and deteriorating public health (Wilkinson and Pickett 2009). These problems are mostly worse in the Englishspeaking cluster among the rich democracies, with the US and the UK ranking first and third on Wilkinson and Pickett's (2009, Figure 1, p 497) widely referenced indicators. Apart from generally lean welfare systems, these countries have all institutionalised pro-employer labour markets, with policy deliberately pushing their populations to depend on overextended labour markets. This dependence is further promoted by sociological processes common to many countries as inequalities related to gender and employment change.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.027 | 0.010 |
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".