How Useful are Work Samples in Validational Studies?
Bibliographic record
Abstract
Some job tasks do not lend themselves to formal on‐the‐job assessment because they do not occur with sufficient regularity to permit the standardized measurement required in validational research. The preparation of incident reports by police and security officers is such a job task. The production of accurate, literate incident reports is important because these reports are often required in legal proceedings. Their standardized evaluation on the job is not practical because incidents occur at unpredictable intervals with highly variable content. Given the limitations of on‐the‐job performance criteria, we developed a standardized work sample by preparing sets of non‐verbal drawings depicting incidents, each of which required a written descriptive report by security officers. A total of 187 security officers completed a cognitive and personality test battery and criterion incident reports based on the standardized materials. Reports supported the usefulness of the standardized work sample, as well as the validity of the test battery – 100% of participants in the upper quartile of the test score distribution produced satisfactory reports, while only 17% of those in the lowest quartile produced satisfactory incident reports. A number of advantages of structured work samples as criterion measures are noted, including their greater standardization, the elimination of range restriction problems by administering them to all job candidates, the opportunity to obtain expert evaluations of work samples at remote sites, and their face and content validity resulting in acceptability to job candidates and to decision makers.
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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 | 0.001 |
| 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".