New Directions in Micro-CSR: How Employees Sensemake, Sell, and React to CSR
Bibliographic record
Abstract
Recent years have witnessed bourgeoning of studies into microfoundations of Corporate Social Responsibility (CSR) examining “the individual actions and interactions underlying any CSR-related practices” (Gond and Moser, 2019: 3). In their scoping review, Gond and Moser (2019) identify two avenues along which micro-CSR have been explored: the psychological and sociological microfoundations. Studies advancing psychological microfoundations have focused on understanding mechanisms underpinning the relationship between employee interpretations of CSR and relevant individual and organizational outcomes (Aguinis & Glavas, 2019; Rupp, 2011; Wang et al., 2020; Zhao et al., 2020). Conversely, studies advancing sociological microfoundations have largely focused on how CSR professionals (such as consultants, sustainability managers, and social issue supporters) act interdependently with other social actors in the organization to create positive social and environmental impacts (Mitra & Buzannell, 2017; Risi & Wickert, 2017; Soderstrom & Weber, 2019). The studies along both avenues have provided us with the view behind the organizational curtain, thereby allowing insight into factors that may hinder or advance CSR. More recently, scholars have advocated for advancing micro-CSR research by moving beyond work-related outcomes grounded in business case for CSR approach and toward investigating the societal impact of CSR (Barnett et al., 2020; Du et al., 2024; Girschik et al., 2020) as well as examining the internal struggles and power dynamics involved in advancing CSR objectives (Deeds Pamphile, 2022; Girschik et al., 2020; Milosevic & Bass, 2024). For example, recent studies have pointed to individual motivation to contribute to social well-being, examining how institutional and community environments shape motivation beyond (and at times in contrast to) organizational mandates (Jasinenko et al., 2024; Milosevic et al., 2023; Stöber & Girschik, 2024). Studies have also begun examining the struggles and power dynamics underpinning CSR, suggesting that considerable relational work and persistence is necessary to advance CSR objectives (Deeds Pamphile, 2022; Sonenshein et al., 2014; Wright et al., 2012). Taken together, these studies suggest increasing complexities of CSR at the individual level, underscoring the intersection of its psychological, environmental, and sociological foundations. The purpose of this symposium, thus, is to advance insight into the dynamism of this intersection through dialogue among scholars studying microfoundations of CSR using different theoretical and methodological approaches. We hope this intermingling of perspectives will foster a rich discussion among presenters and attendees about the individual presentations and their research questions and how studies of sociological and psychological microfoundations may cross-fertilize and collaborate. To promote this learning and discussion, this symposium brings together a wide range of viewpoints, angles, and methodologies within the micro-CSR discipline. These include: 1) Experienced and emerging scholars from both the psychological and sociological traditions from universities across the globe; 2) A variety of CSR actions and contexts, such as biophilic workplace design, CSR actions in hazardous industries, and approaches to CSR in Vietnam; and 3) Diverse methodological approaches, including interviews, multi-level archival data, experiments, and panel data. Alignment of CSR Efforts on Employees’ Social Cohesion Author: Duygu Biricik Gulseren; York University Author: Monika E. Von Bonsdorff; University of Jyväskylä Author: Joseph Yestrepsky; Bowling Green State University Author: Matt Piszczek; Wayne State University Connecting with Nature and Pro-Environmental Behavior at Work Author: Ted A. Paterson; Oregon State University Author: Jay Hardy; Oregon State University Internal CSR Initiatives and Burnout: A Psychological Contract Approach Author: Joseph Yestrepsky; Bowling Green State University Searching for Refuge in Technicalities: Exploring How Oil and Gas Industry Insiders Sensemake CSR Author: Erin Bass; University of Nebraska at Omaha Author: Ivana Milosevic; College of Charleston The T(w)alking of Localized CSR Talk through non-Western Proverbs Author: Mai Chi Vu; Monash Business School Author: Hyemi Shin; Royal Holloway, University of London
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.017 | 0.038 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".