Introduction to International Perspectives on Policies, Practices and Pedagogies for Promoting Social Responsibility in Higher Education
Bibliographic record
Abstract
Abstract We are living in challenging times when the world is fighting to survive the impact of climate changes, growth of pandemics, an unprecedented flow of migrant population, war and destruction. We are also witnessing the phenomena of globalization, economic and technological growth, which are also leading to various opportunities for growth. The desire for inclusive education, equality in accessibility and sustainability has led to responsible and accountable organizations of higher education. Business houses, along with international agencies and institutions of higher education, are now putting their heads together to find a solution to societal and environmental problems. They are often engaged in debating, drafting policies and involving in active research while investing in implementing and communicating issues pertaining to corporate social responsibility (CSR) and sustainability (Vogel, 2005). The concept of CSR has grabbed the attention of media, academia, national governments, intergovernmental organizations and non-governmental organizations. Universities are no longer functioning in isolation but are getting prepared to accommodate and be a part of social change by actively involving students in community life and not confining them to classroom teaching as the only means of teaching–learning method (Sengupta, Blessinger, & Yamin, 2019). This book aims to explore scientific literature pertaining to the subject of social responsibility (SR) and theoretical positions on social ethics and the value orientation of the institutions of higher education. Policies and practices used in various institutions are cited as case studies which give us an insight into the cultural environment of the organization, which is essential to embed SR into the curriculum. Policies and pedagogies that are based on inculcation of SR can lead to the social and economic benefit of students and society at large. While no one approach is prescribed as the benchmark, the chapters help us to understand the practices that academics are implementing in India, Nigeria, Canada, New Zealand and the United States.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".