Political dependence, social scrutiny, and corporate philanthropy: Evidence from disaster relief
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 explores why and how firms respond to social demands through philanthropic giving in the context of a severe natural disaster. Drawing on Marquis and Qian's organizational response model to government signals, we integrate resource dependence theory and institutional theory to build a two‐step model of organizational response to social needs, in situations of disaster relief. We argue that firms depending more on the government for support are more likely to donate in disaster relief, while firms who receive more scrutiny from the government and the general public and firms having more slack resources are likely to donate more. Evidence from Chinese listed companies' donations to the 2008 Sichuan earthquake largely supports our predictions. This study provides a more precise understanding of the corporate philanthropic decision process, decoupling the drivers of philanthropic giving, and those determining the amount given. Theoretical and practical implications are suggested.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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