Quantifying Organizational Ability at Manufacturing Plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We validate the use of a three-stage approach using data envelopment analysis (DEA) for quantifying organizational ability and relating it to operating performance for a large sample of manufacturing plants operating in Canada. In our first stage, we apply DEA to obtain relative plant efficiency based on plant output (sales revenue) and inputs that include various labour quantities, representing different productive activities, and non-labour operating costs. Our second stage relates relative plant efficiency obtained in the first stage to plant characteristics that may influence plant efficiency to obtain the residual value as a measure of organizational ability. In our third stage, we relate the plant cost ratio in t + 1 to the measure of organizational ability obtained for period t and document that plants with higher organizational ability achieve lower future cost ratios. Our analysis adds new insights about the determinants and implications of organizational ability at the establishment level.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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 it