How Do Individuals Judge Organizational Legitimacy? Effects of Attributed Motives and Credibility on Organizational Legitimacy
Bibliographic record
Abstract
This experimental study examines individuals’ legitimacy judgments. We develop a model that demonstrates the role of attributed motives and corporate credibility for the evaluation of organizational legitimacy and test this model with an experimental vignette study. Our results show that when a corporate activity creates benefits for the firm—in addition to social benefits—individuals attribute more extrinsic motives. Extrinsic motives are ascribed when a corporation is perceived as being driven by external rewards as opposed to an altruistic commitment to a social cause. Extrinsic motives negatively affect corporate credibility and organizational legitimacy judgments. This article contributes to a better understanding of the complex process of organizational legitimacy judgment by shedding light on the individual’s perspective and expounding the relationship between attributed motives, corporate credibility, and organizational legitimacy.
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How this classification was reachedexpand
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".