Living Alone in the City: Differentials in Subjective Well-Being Among Single Households 1995–2018
Bibliographic record
Abstract
Abstract Over the past decades, the number of single households is constantly rising in metropolitan regions. In addition, they became increasingly heterogeneous. In the media, individuals who live alone are sometimes still presented as deficient. Recent research, however, indicates a way more complex picture. Using the example of Vienna, this paper investigates the quality of life of different groups of single households in the city. Based on five waves of the Viennese Quality of Life Survey covering almost a quarter of a century (1995–2018), we analyse six domains of subjective well-being (satisfaction with the financial situation, the housing situation, the main activity, the family life, social contacts, and leisure time activities). Our analyses reveal that, in most domains, average satisfaction of single households has hardly changed over time. However, among those living alone satisfaction of senior people (60+) increased while satisfaction of younger people (below age 30) decreased. Increasing differences in satisfaction with main activity, housing, or financial situation reflect general societal developments on the Viennese labour and housing markets. The old clichéd images of the “young, reckless, happy single” and the “lonely, poor, dissatisfied senior single” reverse reality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".