Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research for All serves authors and readers who have a strong interest in different ways of knowing, and we have already discussed the language and writing styles adopted by authors sharing their perspectives Here, we consider the investment of time required for the task of understanding and sharing orally different ways of knowing. Academic knowledge develops through formal studies to offer new ideas and theoretical understanding supported by empirical observations and codified analyses of how entities relate to each other -how the world generally fits together. More often, our understanding is not of the world generally, but of where or how we live in particular. We rely on our implicit understanding of local issues based on impressions and priorities, about how things are done by individuals and organizations, and changes over time. We tend to navigate our day-to-day personal lives by relying on tacit knowledge accrued through experience and familiarity with our immediate surroundings. Academics are steeped in planned observation and systematic analysis, many community organizations are steeped in change making, and schoolteachers and public engagement professionals (both feature in this issue) rely on valuable communication 'know how'. We all have different windows through which we make sense of the bigger picture.
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.
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 | 0.026 | 0.099 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 it