Tackling Grand Challenges: Insights and Contributions From Practice Theories
Bibliographic record
Abstract
This curated debate discusses the value of practice theories in studying, understanding and tackling grand challenges. Practice theories assume that social phenomena are constituted through everyday doings and sayings. Building on this premise, the different contributions in this curated debate go beyond the assumption that grand challenges are abstract phenomena. The authors argue that grand challenges are enacted through mundane, situated actions that are often hidden in plain sight. Building on their research, they suggest that understanding grand challenges requires scholars to approach phenomena as nondualistic. Accordingly, they reveal that situated actions are not self-contained but related across space and time, requiring scholars to adopt a relational perspective. The debate concludes with a call for action as we embrace our dual role as scholars and citizens.
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 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 | 0.029 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.008 | 0.072 |
| Scholarly communication | 0.021 | 0.036 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".