The organizational fitness navigator: enabling and measuring organizational fitness for rapid change
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
In today's fast-evolving environment, dynamic capabilities for the management of organizational change are regarded as being crucial for business survival and improved performance. Although dynamic organizational capabilities have been receiving intense scrutiny from researchers and practitioners over the past few years, relatively little attention has been directed toward creating a systemic model of dynamic capabilities and toward the question of how to effectively measure what the authors call organizational fitness capabilities. This article builds on the concepts of organizational fitness and its profiling (OFP), and proposes the organizational fitness navigator (OFN) as a systemic model of dynamic organizational capabilities. Part of the OFP model is a systemic scorecard (SCC) as a measurement tool for organizational fitness – in contrast to the well-known balanced scorecard (BSC) – for managing rapid change and improving business performance in increasingly networked environments.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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