An Analysis of Innovation in Oil and Gas Projects
Why this work is in the frame
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Bibliographic record
Abstract
We examine the effects of predictors from the firm, project, and individual levels on innovative behavior within oil and gas projects. The theory and propositions tested in this study stem from extant work on (1) innovation in poor performance conditions and (2) the availability of slack resources. The research findings revealed that innovative behaviors were present regardless of size, type, and project performance level. Further, it appears that the relationship between slack and innovation depends on when the innovation is introduced (i.e., when project performance is ahead of, or behind, a plan). Finally, the existence of innovation in (1) under-performing projects did not appear to exert any influence on project outcome, and (2) over-performing projects appeared to exert a negative influence on project outcome.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| 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