Application of the Logit Model to the Analysis of Economic Activity Factors of the Disabled
Bibliographic record
Abstract
The purpose of this study was to identify factors affecting the classification as a working group of economically active people with disabilities. According to the Labour Force Survey methodology, working population is defined as labor resources, labor supply and labor force, which includes all people of working-age 15 and older, considered as employed or unemployed. Community of people with disabilities is extracted from the general population aged 15 and more, on the basis of law. People with disabilities include those aged 16 and over who have been awarded a judgment about the degree of disability or inability to work (CSO 2011).In the analyses of the labor market models with qualitative variables, which include logit models, are very often used. For the purpose of the study it was assumed that these models will describe the probability of a person with a disability to qualify for the category of employed. The basis for estimating probability models were individual data obtained under representative Labour Force Survey in the fourth quarter of 2010. A set of explanatory variables contains 54 binary variables.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".