Corporate Social Responsibility Communication In Western Balkans Banking Industry: A Comparative Study
Bibliographic record
Abstract
The purpose of this paper is to study corporate social responsibility (CSR) reporting activity in the Western Balkans (WB) banking industry. The first aim of the study is to measure the level of CSR reporting activity of banks within Western Balkan Countries (WBC), and the second is to compare the results within WBC and with other countries and regions in the world. We apply the method of content analysis to measure the CSR reporting activity of all licensed banks in WB actively operating until May 2019. Findings indicate that almost half of the banks from WB do not disclose any social responsibility information on their websites. Only a small number of banks prepare independent CSR report, while almost half of the banks who have CSR disclosure, report their CSR initiatives through a web link/heading. One-quarter of the banks report their CSR activities within their financial or annual report. External disclosures are most frequently reported. The category of community involvement is the most frequently reported, while the second most reported CSR activity is under the category of environment. The regression analysis revealed that the size of the banks represented in terms of total assets is a modest predictor of the level of CSR reporting. The paper contributes to the scarce literature of CSR reporting in the banking industry from WB. The results from this study can help academic researchers, business practitioners and policymakers to better understand the phenomenon of CSR communication in the banking industry in the region of WB.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".