Work integration of people with severe mental illness in social enterprises
Bibliographic record
Abstract
Lack of employment and short job tenure are still a major issue for people that suffer of a severe mental illness. One of the main issues in the rationale for this thesis was the opportunity to deeply investigate and better understand why getting and sustaining a job for this population is so difficult and challenging. In particular, we focused on individual and environmental factors associated with the work integration of people with mental illness employed in Italian social enterprises and that can be significant determinants of job tenure for this group. The thesis outlines in the first two chapters the presentation of the survey development and design of the study, an overview of the historical perspective on mental health and of related Italian legislation, as well as a description of psychiatric and vocational services for people with severe mental illness. In particular, a special attention is given to the presentation of the social enterprise model. After that, a review of previous research on determinants of job tenure for people with severe mental illness is presented. The main results of each study conducted are presented in the results part, which is a collection of papers. In particular, Study 1 is designed with the main aim of establishing the profiles of employees that suffer of a severe mental illness working in Italian social enterprises, as well as to investigate potential differences across people with different psychiatric diagnosis on psycho-social variables linked to the person and linked to the work. Study 2 proposes the validation of two scales, the Motivation to Find a Job scale in a sample of mentally ill workers enrolled in supported employment programs located in Canada, and the Motivation to Keep a Job scale among people with severe mental illness employed in Italian social enterprises. In Study 3 we investigate the relationship between individual characteristics, features of the workplace environment and job satisfaction in people with severe mental illness. In addition, it is our intent to explore the spectrum of workplace accommodations available for employees with mental disabilities working in social enterprises, and the impact of those accommodations on job satisfaction, taking into account the individual characteristics of these employees. Study 4 aims at examine the validity of work engagement in people with severe mental illness.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".