When Corporate Social Responsibility (CSR) Meets Organizational Psychology: New Frontiers in Micro-CSR Research, and Fulfilling a Quid Pro Quo through Multilevel Insights
Bibliographic record
Abstract
Researchers, corporate leaders, and other stakeholders have shown increasing interest in Corporate Social Responsibility (CSR)—a company’s discretionary actions and policies that appear to advance societal well-being beyond its immediate financial interests and legal requirements. Spanning decades of research activity, the scholarly literature on CSR has been dominated by meso- and macro-level perspectives, such as studies within corporate strategy that examine relationships between firm-level indicators of social/environmental performance and corporate financial performance. In recent years, however, there has been an explosion of micro-oriented CSR research conducted at the individual level of analysis, especially with respect to studies on how and why job seekers and employees perceive and react to CSR practices. This micro-level focus is reflected in 12 articles published as a Research Topic collection in Frontiers in Psychology (Organizational Psychology Specialty Section) titled “Corporate social responsibility and organizational psychology: Quid pro quo.” In the present article, the authors summarize and integrate findings from these Research Topic articles. After describing some of the “new frontiers” these articles explore and create, the authors strive to fulfill a “quid pro quo” with some of the meso- and macro-oriented CSR literatures that paved the way for micro-CSR research. Specifically, the authors draw on insights from the Research Topic articles to inform a multilevel model that offers multiple illustrations of how micro-level processes among individual stakeholders can explain variability in meso (firm)-level relationships between CSR practices and corporate performance. The authors also explore an important implication of these multilevel processes for macro-level societal impact.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.027 |
| Scholarly communication | 0.021 | 0.026 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".