Benefitting from IS Research -- Who and How? A Panel on the Value of IS Research
Bibliographic record
Abstract
The aim of this study was to investigate how dichotomising three-graded ADL Staircase data affects the possibility of detecting changes in ADL dependence between different assessment occasions. An authentic two-occasion data set was used as a basis for a simulation experiment. In all, we used four different data treatment principles, all utilising the matched pairing of the data. The first principle utilised a sum score technique, and the second within-person comparisons by means of item-by-item analysis of improvement or deterioration. The third principle used ADL ranks, a novel approach, while the fourth used within-item ranks. Independently of the data treatment principle used, the statistical power of all tests was reduced by 13-24% after dichotomisation, compared to when the three-graded scale was utilised. The results indicate that dichotomising ADL Staircase data results in information loss, and hence in reduced ability to detect changes. The need to consider the purpose of the ADL assessment before reducing the number of scale steps is highlighted. The knowledge generated in this study is useful for practitioners and researchers, aiming at evaluating rehabilitation interventions.
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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 | 0.007 | 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 | 0.001 | 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) | 0.003 | 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".