A qualitative study on leadership and corporate social responsibility in an emerging economy
Bibliographic record
Abstract
The previous research relating to CSR and mindfulness leadership, for the purposes of this study, provides an intersection where both backgrounds come together to invite an opportunity for collaboration. The most critical factor in the implementation of CSR is the development of leaders for a sustainable global society as mindfulness should be relevant to the achievement of organizational and leadership objectives. It is here that we find the inspiration for the current study and the relevance of the research query endeavoring to discover if the framework of mindfulness leadership could prove an effective driver for CSR? For this reason, 20 in-depth interviews were conducted from the middle level managers working in an emerging economy - Pakistan. The conceptual framework of leadership theory guided this study’s investigation as it brought to the forefront certain challenges facing organizational leaders endeavoring to facilitate CSR objectives; and explored if the application of mindfulness leadership could prove an effective leadership framework for successful CSR engagement. This supporting data coupled with the study’s interview of executive leaders, across industry lines, familiar with CSR initiatives, lent to certain analytical insight that identified mindfulness leadership as a framework for organizations to facilitate the accomplishment of CSR objectives.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".