Conceptualizing Generous Scholarship
Bibliographic record
Abstract
In an era of neoliberalism and the COVID-19 pandemic, it is imperative to revisit the meaning, value, and praxis of scholarship. This article documents exploration of the emerging concept of generous scholarship, a compelling yet ill-defined and undertheorized construct that inspires our scholarly practices. We analyze the extant literature about generous scholarship and related constructs to address three guiding research questions: What is generous scholarship? What are its actions? What are its implications for scholarly life and the academy? A descriptive theory-generating research design led to a robust conceptual framework involving five principles of generous scholarship: social praxis, reciprocity, generous mindedness, generous heartedness, and agency. Generous scholarship is an intentional, collegial approach to scholarship that helps to mitigate the sense of isolation and depletion of energy often associated with managerial, production-oriented academic contexts. We argue that individuals and institutions that embrace generous scholarship may attract and nurture a vibrant cadre of academics, replenished in mind and spirit. Academics, university administrators, and higher education policy-makers are encouraged to address or resist the pressures inherent in their current workplaces and to carve space for generous scholarship.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.010 | 0.072 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".