Nexus between corporate social responsibility and earnings management: Sustainable or opportunistic
Bibliographic record
Abstract
This study examines the association between corporate social responsibility (CSR) and earnings management (EM) among manufacturing firms from a developing economy, Pakistan. To deal with the CSR measurement and data bias, a multimethod approach has applied to measure CSR (both qualitative and quantitative approaches). This research has also established CSR disclosure indices and CSR monetary spending ratio (CSR MSR). Moreover, this research examines both types of EM (accrual‐based as well as real activities‐based) and used annual data set from 2009 to 2018 for 160 nonfinancial firms. For empirical analysis, the two‐stage least square (2SLS) and pooled ordinary least square (POLS) regressions are used. This study finds a negative relationship between CSR and EM, and it supports the notion that firms' commitment to CSR is largely driven by long‐term perspective. However, with respect to each measure of EM and CSR, this relationship is asymmetric.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".