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
Most ethics boards classify children as a vulnerable population -- all children. The reason given for this is that children lack the necessary cognitive capacity to decide whether or not to participate in most research. It may be difficult for them to foresee the risks and potential benefits to their own well-being or to understand how the conditions of research may or may not be in their own best interests. Children who have special challenges, such as those with dyslexia, ADHD, developmental delays, or mental health issues, or children living in poverty, who may be illiterate or repressed, may have even less capacity to understand and give assent to participate in research. Working with and for children, which is the cornerstone of the child-computer interaction community, raises a number of ethical challenges. First, we must present our research to children in ways they can understand. Because if we don't do this then we exclude the children who could benefit the most from the work we do, because they cannot easily give assent or because they may be difficult to access or work with. This raises an even more important issue. We may think that children can benefit from participating in our research or from using the computational systems that result from our research. But is this true? How do we know if the children we study are benefiting from our research? Third, what happens after our research is over? What legacy do we leave behind when our research is complete?
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it