Bibliographic record
Abstract
This paper presents the development of an instrument for measuring strategic control systems (SCS). Although SCS has received considerable attention in the literature, most of the discussions, on the elements that constitute SCS, are limited to descriptive statements. Thus, the theoretical construct of SCS suffers from lack of extensive statistical validation procedures. However, there are a few authors that had initiated the development of an instrument to measure the SCS. Their small effort had also been criticized due to the inconsistency among authors in defining SCS, which would likely affect the validity of the instrument being developed. Given this lacuna, this paper has developed and validated an instrument for conceptualizing SCS, specifically under the environment of Quality Management strategy. Based on a careful and systematic process of instrument development, this paper revealed that SCS consists of two important dimensions, namely strategy implementation and strategic resource allocation. In developing this instrument, a total number of 205 respondents were involved. The findings reported in this paper would benefit future researchers in measuring SCS, particularly for survey-based research.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| 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 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".