Legacies of Logics: Sources of Community Variation in CSR Implementation in China
Bibliographic record
Abstract
This paper explores how legacies of past logics spawn variation in the institutional landscapes of different geographic regions in China. Of particular interest is how this variation influences the ways that actors interpret and respond to broader societal and world society pressures. Employing a cross-level comparative research design, we examine the enduring legacies of previous state logics, which have given rise to distinctive material and symbolic resource environments in different regional communities across China. To the extent that institutional contexts direct the attention of actors toward particular environmental stimuli and provide the symbolic and material resources to respond, a better understanding of how contexts differ provides more accurate causal explanations of the variability of organizational behavior. We explore this phenomenon in the context of recent government-mandated corporate social responsibility (CSR) initiatives in China. Our examination of public and private CSR initiatives, along with the CSR activities of a sample of 714 listed Chinese companies, suggests that legacies from past state logics become embedded in local institutional infrastructures and shape how abstract, multifaceted CSR initiatives are interpreted and implemented.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".