A dynamic model of responsible leadership roles in hybrid organizations
Bibliographic record
Abstract
Purpose Responsible leadership (RL) is an approach that enables companies to consider stakeholder interconnectedness more extensively when addressing significant social and environmental challenges. This theoretical concept remains ambiguous and has received scant empirical attention. This article aims to better understand the practice of RL through the experience of hybrid organization leaders by answering two questions: (1) who are the most significant stakeholders from the standpoint of responsible leaders? and (2) How do these leaders describe their role vis-a-vis these stakeholders? Design/methodology/approach Semi-structured interviews with 12 leaders of B Corp-certified companies in Quebec were conducted to trace each company’s lifecycle, to identify their main stakeholders over time and to identify the behaviors that CEOs adopted toward these stakeholders. In light of the experience described by the B Corp CEOs, existing theoretical models are contrasted with practice. Findings The discussion suggests that the main stakeholders targeted by the CEO behaviors identified are employees, customers and the community. Seven main RL behaviors are highlighted. We propose a new conceptual model that connects these different RL roles along two complementary axes: structuring and facilitating roles. Originality/value A new dynamic model representing these interrelated roles is proposed. This model contributes to a better definition of responsible leadership within companies committed to sustainable development. It also serves as a frame of reference to help their leaders, and those who train them, to identify behaviors to develop.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".