Modeling mouse, human, and discipline: Epistemic scaffolds in animal behavior genetics
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
Animal models of human disorders are a ubiquitous feature of contemporary biomedical research, but how is their value and role in understanding human disorders established? This article examines the dynamics of building up (and sometimes knocking down) claims about what a model can demonstrate in the field of animal behavior genetics. Drawing on long-standing analogies that describe scientific knowledge production as a process of construction, I introduce the metaphor of an ‘epistemic scaffold’ to illuminate how scientists create and contest claims about the utility of animal models. The flexible, temporary nature of scaffolding draws attention to the processes of building up claims to increasingly risky heights and reconfiguring the evidence supporting particular models by including or excluding particular facts and claims. As researchers include or exclude observations from epistemic scaffolds, to contest or build up different links, they gradually frame human disorders. Negotiations over how much to claim about the utility of animal models also reflect larger tensions in the discipline concerning what animal studies reveal about human disorders.
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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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