The Service and Outcome Measurement
Bibliographic record
Abstract
The Service and Outcome Measurement System (SOMS) was de-veloped by Human Resources Development Canada (HRDC) to be a tool for promoting employment. SOMS was intended to help frontline staff in local public employment service offices counsel job-seekers about the best strategies for gaining employment and to assist analysts and managers in determining the best employment and/or training strategies for specific client groups. A microcomputer-based prototype of SOMS was built in 1994. It had three main elements: 1) a relational database of client specific information for employment insurance bene-ficiaries and/or participants of HRDC employment or training pro-grams, 2) a means for examining the results of past services provided by the public employment service, and 3) a computerized model to pre-dict what services would most benefit a particular job-seeker. In 1997, an algorithm was added to SOMS for predicting what service would best promote employment among groups defined by geographic and
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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 | 0.010 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".