Societal Impacts of Higher Education Research: From ‘Publish or Perish’ to ‘Publish and Prosper’ in Business School Scholarship
Bibliographic record
Abstract
This paper introduces a transformative systems-level framework for understanding the interplay of institutional, cultural, and systemic dynamics influencing the societal impacts of academic research. We introduce and apply the Societal Impacts of Research Institutional Ecosystem (SIRIE) framework to business school scholarship and academic research in higher education. The United Nations Sustainable Development Goals (SDGs) serve as SIRIE’s normative ethical framework to benchmark: institutional mission; accreditation bodies’ compliance requirements; faculty tenure and promotion research expectations; the influence of rankings and ratings; and journal quality metrics. Our framework acknowledges the role the Anthropocene Epoch plays in contributing to contemporary social and environmental problems. We argue that recalcitrant institutional forces in academia neutralize the promise of academic scholarship to galvanize meaningful societal impacts. We assert that the contemporary state of higher education research is unfortunately dominated by a “publish or perish” mentality. This narrative produces academic research that is decontextualized from today’s exigent “grand challenges” related to poverty, climate, equity, health, peace, environment, etc., as well as transformative solutions for a sustainable future. By exploring an alternative paradigm for academic research through SIRIE and the SDGs—“publish and prosper”—we detail how academic research can meaningfully contribute to change the world for the better.
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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 | 0.009 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".