Greening organizations through leaders' influence on employees' pro‐environmental behaviors
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
Summary Climate change is a serious global issue that poses many risks to environmental and human systems. Although human activity is cited as the main cause of climate change and organizations significantly contribute to climate change, research that investigates workplace pro‐environmental behaviors remains scarce. We develop and test a model that links environmentally‐specific transformational leadership and leaders' workplace pro‐environmental behaviors to employees' pro‐environmental passion and behaviors. Structural equation modeling on data from 139 subordinate–leader dyads ( M ages = 37.42 and 40.17 years, respectively) showed that leaders' environmental descriptive norms predicted their environmentally‐specific transformational leadership and their workplace pro‐environmental behaviors, both of which predicted employees' harmonious environmental passion. In turn, employees' own harmonious environmental passion and their leaders' workplace pro‐environmental behaviors predicted their workplace pro‐environmental behaviors. These findings show that leaders' environmental descriptive norms and the leadership and pro‐environmental behaviors they enact play an important role in the greening of organizations. Conceptual and practical implications are discussed. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.011 | 0.001 |
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