The Management of Accountability for Innovation in an Organization
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 suggested comprehensive three-step method for management of the employees’ accountability for innovation is aimed at intensification of the innovation activity in an organization. The innovation process is characterized by suitability, feasibility, and applicability of the ideas. It is performed by the phases: finding new ideas, evaluation of ideas, development of ideas including their experimentation and implementation. Change of the innovation process characteristics causes the need of the accountability management. As a result of the management, the accountability characteristics such as a sphere, a level, and a measure of the employees’ accountability for innovation are changed. The method is realized by sequence of the steps: setting accountability, evaluating accountability, and managing accountability. The steps are aligned with the innovative process phases. At the first step, the spheres and the levels of employees’ accountability for generating ideas are set. At the second step, the spheres, levels, and measures of employees’ accountability for development of the ideas are determined. The measure of accountability characterizes accountability of the members of the dynamic and heterogeneous group which is self-formed by employees as a result of the idea assessment. It is set equal to the idea value. The idea value is calculated by summation of assessments of the innovative process characteristics. At the third step, the spheres, levels, and measures of employees’ accountability while development of the ideas are guided. Sharing accountability among the group members is based on their knowledge and skills. The preferable innovation direction and the key idea are revealed.
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 | 0.000 |
| Science and technology studies | 0.000 | 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