An empirical investigation of the Malcolm Baldridge National Quality Award framework using causal Latent Semantic Analysis
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
Numerous studies have investigated the linkages implied in the Malcolm Baldrige National Quality Award (MBNQA) framework. Those studies posited that the MBNQA quality experts defaulted to the premise that each construct is related to all others in the MBNQA framework because of the lack of specific knowledge about the causative relationships. Therefore, there is a need for both academicians and managers to explore the MBNQA framework as a non-recursive causal model as it was originally developed. This study uses a causal latent semantic analysis methodology to test the MBNQA as a non-recursive causal model using textual data obtained from scholarly MBNQA publications. Though the MBNQA framework is yet to be fully explored by both academicians and practitioners, this is the first study to show that the cumulative finding of prior research supports the contention that the constructs in the framework have substantial influence on each other.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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