Strategic Orientations: Multiple Ways for Implementing Sustainable Performance
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
The Four Phase Model®, created by prof. dr. Teun W. Hardjono [1] in 1995, distinguishes four ideal type strategic orientations and shows that these strategies brighten and dim in a specific sequence, adding the most required competences to the organization, and creating a natural rhythm to corporate dynamics. By applying this theory one can understand the nature and whereabouts of the organization’s systemic constraints, revealing the basic features for creating a roadmap towards sustainable performance improvement and competence development. The model generates the top priorities, selects the most adequate (ideal type) interventions and key performance indicators. Combining strategic “situations” as indicated by the Four Phase Model and phase-wise “contexts” as introduced by Spiral Dynamics [2], provides a conceptual synergy with four innovative outcomes: Firstly, aligned with specific contexts, the strategic interventions and KPI’s can be made more specific and practical, thus creating a roadmap for performance improvement and organizational development. Secondly, it structures change management into four distinctive hierarchical complexity levels: 1) enhancing fundamental skills, structures and procedures (vitalizing); 2) improving contemporary levels, aligned with the dominant value system (optimizing); 3) new re-orientations while continuing within current systems (shifting) and 4) a transformation to a more complex context or emerging value system (transforming). Thirdly, powered with the combined understanding of above concepts, one can deduct the specific context and situation for each intervention, instrument or approach to be applied effectively. Fourthly, the combination provided the bases for the so-called Strategy Scan and Strategic Sustainability Scan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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