Demographic Aspects of Illiteracy in Italian Regions through the Latest Census Data
Bibliographic record
Abstract
The level of education is becoming more and more important in order to explain the variations in the demographic phenomena. In fact, many studies have shown that women with a high level of education have fewer children; higher education is associated with lower mortality and better health. These evidences are already consolidated in the recent international literature and, according to many scholars, the variable education wiIl be at the center of the social demography of the 21 st century. In this context the analysis of illiteracy would allow to grasp some critical issues related to the transformations taking place in society. We recall that in Italy the community of statisticians and demographers, apart a brief interlude in the fifties and sixties of the last century, gave little importance to the study of illiteracy, considering it a residual element of the social development of the country. Instead, pedagogues and linguists, because of their direct involvement, have shown that in Italy illiteracy and functional illiteracy are in various ways widely spread and cause social marginalization. At national level these phenomena are widely investigated thanks also to international surveys involving Italian country, such as the International Adult Literacy Survey coordinated by Statistics Canada and those conducted by the OECD. Going down to the Italian regional level, the immediately available data are those provided by the censuses which, however, have the limit of not explicitly bringing out these new forms of lack of adequate education, because only "illiterate being able to read or write. In the census, illiterate and unskilled literates are labeled as those with no educational" and "alphabets but without a qualification" are detected. In the analysis developed here these two categories have been grouped because in this way we believe we could estimate some important features of functional illiteracy at regional level, a phenomenon that is largely underestimated today.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".