The Institutionalization of CSR: At the Crossroads of Home and Host Countries Institutional Settings, Multinational Corporations, and Multinational Institutions
Bibliographic record
Abstract
Abstract Purpose This chapter examines the institutional configuration of internal CSR in MNCs operating in Canada and Brazil, as well as headquarters-subsidiary relations within the institutional settings of their home and host countries. Methodology/approach The institutional logics perspective is used as it provides a systematic approach to understanding the institutional orders at play in the development of soft policies. Findings Whereas the institutional framework of the host country is a key factor in the regulatory and distributive spheres, the spheres of discretionary spending and soft policies are largely influenced and shaped by the MNCs through self-regulation, and may also be guided by intergovernmental institutions and NGOs. Research limitations/implications The empirical data is limited to two case studies. It seeks to understand the multiple facets of CSR reality and produce contextual insights. Generalizations might fit better with other context communities – research subjects and the researchers who investigate them, beyond the mining industry – in a non-positivist, non-probabilistic sense, than with other context settings within the same industry. Practical implications The chapter concludes that institutional discourses and practices around internal CSR seek to strengthen a firm’s legitimacy. CSR does not necessarily increase the MNC’s performance when viewed in a market logic, but its operational viability can align with the corporation’s global strategy and identity. It also highlights resistance resulting from professional and community institutional logics. Originality/value This chapter contributes to the literature on internal CSR and is original in including an MNC from the South with subsidiaries in the North.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".