Bibliographic record
Abstract
Back to table of contents Previous article Next article Association NewsFull AccessAPA's Workplace Collaboration Provides New Online ToolMary Claire LeftwichMary Claire LeftwichPublished Online:4 Jan 2008https://doi.org/10.1176/pn.43.1.0009aThe Partnership for Workplace Mental Health, a program of the American Psychiatric Foundation, has launched Employer Innovations Online, a Web-based, searchable database that profiles employers' innovative policies, programs and practices for addressing mental health. It can be accessed at .Employer Innovations Online is the latest expression of the Partnership for Workplace Mental Health's commitment to advancing effective employer approaches to mental health. As APA President Carolyn Robinowitz, M.D., explained, "The partnership focuses on helping employers understand the business case for addressing mental health at the workplace. Employer Innovations Online helps employers translate that understanding into action by highlighting case examples of successful company approaches."This resource, which is easily navigated and user friendly, describes the actual practices of leading companies in key areas, such as screening and education, employee assistance programs, disability management, community partnerships, and wellness programs. Each entry, or case study, in the database describes the practices of one employer, such as American Airlines, Cisco Systems, DuPont, JPMorgan Chase, Pitney Bowes, PPG Industries, and Sprint. Users have the option of searching by employer name, type of program, number of employees, type of industry, or geographical region.The business case for addressing mental health has evolved in recent years. Employers are increasingly saying to the partnership, "We get it. Not addressing mental health is costly. What do we do about it?" This tool was developed in direct response to that question.The Partnership for Workplace Mental Health invites employer participation in this new project. Interested companies and organizations can submit their innovative approaches to workplace mental health online at , or contact Leftwich at (703) 907-8561 or [email protected]. Those interested in more information about the database or the partnership are welcome to call Leftwich as well. ▪Mary Claire Leftwich is the program associate for the Partnership for Workplace Mental Health. ISSUES NewArchived
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.889 | 0.788 |
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".