The <scp>K</scp>nowledge, <scp>S</scp>kill, and <scp>A</scp>bility <scp>R</scp>equirements for <scp>T</scp>eamwork: <scp>R</scp>evisiting the <scp>T</scp>eamwork‐<scp>KSA T</scp>est's validity
Bibliographic record
Abstract
The Teamwork – Knowledge, Skills, and Ability (KSA) Test was developed by Stevens and Campion to operationalize their comprehensive taxonomy of teamwork competencies. The test is generally considered ‘valid’ and has been used frequently in organizations. Our review of the literature found an average criterion validity of.20 for the Teamwork‐KSA Test, although there was considerable variability across studies. We could find no research on the item properties, factor structure, or subscale reliabilities, and no extensive investigations of the nomological net of this test. In our field sample, we found subscale reliabilities to be generally inadequate, no meaningful factor structure, and low predictivenes of employees' performance on team‐related dimensions. Although the taxonomy it purports to measure is preeminent, the Teamwork‐KSA Test itself may have serious limitations.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".