DECOMPOSING GAPS BETWEEN ROMA AND NON-ROMA IN ROMANIA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract It is widely known that the Roma have been suffering persistent disadvantages. Yet, little empirical evidence exists. Using the censuses of 1977, 1992, 2002, and 2011, I provide a comprehensive overview of the past, present, and an outlook on the future of the Roma in Romania, home to a large and rapidly growing Roma community. Young Roma, in particular girls, are less likely to be attending school, indicating that lack of educational attainment is likely to persist. The Roma have worse housing conditions and face lower employment and higher unemployment levels. Amongst Roma, females are less likely to be employed than males. Oaxaca–Blinder decompositions of the ethnic and gender employment gaps reveal that the differences in employment cannot be fully explained by observables, such as age or education. Despite the seemingly dire picture, there are signs of improvement for more recent cohorts, as literacy rates have reached close to universal levels.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it