An Overview of Economic and Social Opportunities and Disadvantage in European Households
Bibliographic record
Abstract
The socioeconomic position one Starts from in life is a key determinant of life chances, as consistently shown by a vast research literature across different disciplines and relating to various industrialized societies. However, that socioeconomic starting point is a far from perfect predictor of outcomes - some people do better, and some worse, from what look to be similar starting points. Furthermore, the price paid by those who do poorly can itself be very different in different societies. So there is much to be learned from the way different societies seek to promote healthy development and minimize the price of failure. The aim of this chapter is to provide an overview of socioeconomic disadvantage versus opportunity in Europe. It is focused in particular on human capital and its relationship to opportunities and disadvantage for individuals and households over the life course. It both draws on recent research and investigates an exciting new source of comparative data, the European Community Household Panel survey (ECHP). This allows an in-depth examination of the countries currently in the European Union (EU), which we put in perspective where possible by drawing on information about a number of countries soon to join the Union, and about Canada and the United States. We begin with an overview of disadvantage and opportunities, two sides of the same coin, in Section 3.1. We describe the extent of poverty in the EU, and more broadly in the rieh countries of the world, and conversely the living Standards and opportunities enjoyed by those who are doing well. There is much to be learned from examination of a snapshot picture, particularly given this comparative perspective, but it is also essential to incorporate the dynamic processes at work over time. We therefore exploit the fact that persistence versus change in income poverty from year to year - albeit over a relatively short period - can also be explored using panel data from the first three waves of the ECHP. Measuring both persistence of low income and direct experience of deprivation allows us to capture the extent and nature of poverty and exclusion much more fully than a measure of current income alone. We then turn to human capital, where we have to rely on educational attainment as an incomplete but widely available indicator.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
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".