Effects of human capital and learning rate: When organizations meet with information distortion and environmental dynamism
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
Abstract This study systematically evaluates the effects of human capital and learning rate under typical organizational contexts with information distortion (i.e., no distortion, individual forgetting, and information misrepresentation) and environmental conditions (i.e., personnel turnover and environmental turbulence). The multi‐agent simulation model reveals that keeping an appropriate learning rate is an efficient way to balance exploration and exploitation. Slow learning outperforms only under the contexts of both no distortion and rare personnel turnover, whereas intermediate and high learning rates are more valuable in other organizational contexts. Moreover, we find that human capital generally has a positive effect on learning performance, with an exception that when an organization faces environmental turbulence, human capital has an inverted U‐shaped relation with learning performance. This study draws implications for managing organizational learning and guiding organizations with different human capital on how to influence learning under various organizational contexts.
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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 | 0.001 | 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 | 0.000 | 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