Myopic Creative Climate - The result of streamlining in R&D organizations?
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
Creative climate has been proposed as a fundamental component of organizations displaying high innovation performance, and validated tools for measuring creative climate are today readily available. In the existing literature, however, the multi-dimensionality of the creative climate concept is not thoroughly reflected, but organizations have primarily been regarded to either have or not have a creative climate. In this article we attempt to bring a more nuanced perspective to creative climate – describing what can be seen as a myopic creative climate. This type of climate is characterized by a good working environment where people support each other’s ideas and trust each other. However the levels of risk taking and idea time are lower and, more importantly, this results in a significantly lower innovation performance than is found in a good creative climate. This alters the way we view creative climate by highlighting that not all dimensions are equally important. Even in a work environment where the majority of creative climate dimensions are at high levels, the organization may suffer from decreased levels of innovation.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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