Bibliographic record
Abstract
Exploring social policy language and concepts Social scientists, historians, and linguists have noted that the terms, metaphors, and concepts we use are far from innocent and are closely tied to political struggles and international exchanges. Therefore, from a comparative and international perspective, studying terminology and concept formation is an important part of both political and policy analysis (Williams, 1976; Sartori, 1984; Farr, 1989; Heywood, 2000; Daigneault, 2012). This is also the case when it comes to social policy. The words we use to make sense of social policy and the way we use them need to be properly studied to get the definitions right while grasping the political consequences of social policy language. But so far, relatively little has been done in that respect. In recent years, researchers have rightly complained about the vagueness of core concepts used in contemporary social policy debates. For example, following well-known predecessors such as Asa Briggs (1973–74, 1985) and Richard Titmuss (1963), John Veit-Wilson (2000, 2003) and Daniel Wincott (2001, 2003) have criticised the tendency among social policy students and practitioners to use the concept of ‘welfare state’ without offering any coherent definition of it. As Wincott (2001: 409) puts it, ‘While the expression of “the welfare state” has many interpretations and connotations – both academic and popular – there are surprisingly few clear discussions of the concept… . [The] field does need to be mapped’. Social policy concepts are subject to many interpretations, partly because they are dynamic historical constructions. Thus, one way to map this field and explore the boundaries of social policy is to take a comparative look at the history of concepts like ‘welfare state’ (Beland, 2011; Petersen and Petersen, 2013). Even though a number of key social policy concepts (such as ‘ Wohlfahrtsstat ,’ ‘ Sozialstaat ,’ or ‘ Sozialpolitik ’) have a German origin, most of the English language discussions on social policy language (for example in Flora and Heidenheimer, 1981; Alber, 1988; Lowe, 1999; Powell and Hewitt, 2002; Titmuss 1963) focus on Great Britain , as it was British Archbishop William Temple (1941) and others who popularised the term ‘welfare state’ during the Second World War, and paved the way for its political breakthrough in the late 1940s (Figure I.1).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 teacher head, 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".