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
Over the last 15 years, the study of technology in classroom settings has highlighted the need for a new research paradigm. Past research on educational technologies and software has been impugned due to the impossibility of establishing valid controls for the simultaneous introduction of technological and pedagogical innovations (Cobb, 2000; Brown, 1992; Collins, 1992, 1999). In response to the growing dissatisfaction to traditional paradigms, a relatively new approach called design research (Brown, 1992; Collins, 1992) has gained popularity – for an extensive history, see Edelson (2002). This new framework provides a potential infrastructure for promoting exchange across many different types of investigation (Cobb et al., 2003). Design researchers are able to use varying elements of design to optimize conditions that may result in the increased efficacy of a given educational innovation, since the process is defined by iterative design and formative research in complex real-world contexts (Edelson, 2002). Through careful observation, both quantitative and qualitative, design researchers are able to surmise how different design elements are contributing to observed results (Collins, 1999).
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 | 0.002 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it