Bibliographic record
Abstract
This article presents estimates of the social minimum in the fourth quarter of 2023. On an annual basis (relative to the corresponding period a year ago), modelled household expenditure grew faster than inflation. The social minimum increased from 8.0% in the household of a parent with a younger child to 10.4% in the working household of a single person, with the consumer price index (6.4%). In contrast, in relation to the previous quarter, the increase in inflation in Q4 2023 was barely notice-able (0.5%) and the values of the social minimum increased from 0.7% (in the household of parents with an older child) to 1.0% (in the working household of a single person). The small increase in the social minimum baskets was mainly due to higher housing and energy me-dia charges. With a low CPI (0.2%), they increased by 1.1% in the model households. Among the housing expenditure baskets, charges for central heating (up by 1.9%) and water heating (up by 1.1%) increased the most, with a CPI for thermal energy of 2.2%). Expenses for cold water and hous-ing services increased by 1.1%. In contrast, the value of food needs increased between 0.2% (em-ployee households without children) and 0.4% (pensioner households), with a slightly higher CPI (0.6%).
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".