Bibliographic record
Abstract
Purpose The purpose of this paper is to examine corporate social responsibility (CSR) activities in Canadian family firms. Design/methodology/approach This paper is an empirical work using a sample of Canadian listed companies for eight years between 2010 and 2017. Findings Relying on five measures for CSR, this paper finds that, compared with other listed firms, family listed firms have a higher level of CSR engagement. Further tests show that family-named family firms engage in more CSR activities; family firms with second largest shareholders engage in more CSR activities; and family firms affiliated with large business groups engage in more CSR activities. However, family firms whose family members are CEOs, presidents or board chairpersons engage in less CSR engagement. Originality/value This paper contributes to the current CSR literature by highlighting the importance of family firm heterogeneity in shaping a firm’s CSR practices. It focuses on four characteristics of Canadian family firms that are potentially connected to CSR, namely, family-named family firms; family firms with family members being CEOs, presidents or chairpersons; family firms with second largest shareholders and family firms affiliated with large business groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".