A bottom‐up approach for productivity measurement and improvement
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
Purpose The steady incline in oil prices combined with the recent credit crisis and downturns in financial markets has driven organizations to re‐evaluate their manufacturing processes and bottom line. The purpose of this paper is to suggest a bottom‐up approach that may be used by firms in planning, managing and forecasting productivity improvements. Design/methodology/approach A multiple‐case study approach was used: two comprehensive cases and seven short cases were used to illustrate the model. Findings The lack of understanding of the relationship between productivity, profitability and performance has led to the application of piece‐meal solutions for problems in productivity. Bottom‐up approach in improving productivity will provide better results than top‐down approach. Originality/value This paper describes the bottom‐up approach which has been successfully used for managing productivity improvement initiatives.
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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 | 0.003 | 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 | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it