Bibliographic record
Abstract
While humans possess a ready capacity to view a target (biological or otherwise) as an intentional agent (i.e. the 'intentional stance'), the conditions necessary for spontaneously eliciting these mentalizing processes are less well understood. Although research examining people's tendency to construe the motion of geometric shapes as intentional has done much to illuminate this issue, due to methodological limitations (a reliance on subjective self-report) this work has not fully addressed the potentially automatic and obligatory nature of mentalizing. Acknowledging this problem, recent research using prelinguistic infants, neuroimaging technology and methods that avoid explicit self-report all provide unique paths to circumvent this shortcoming. While work of this kind has generally corroborated the results of previous investigations, it has also raised a number of new issues. One such issue is whether spontaneous mentalizing processes for abstract non-biological stimuli are instantiated in the same neural architecture as those for realistic representations of intentional biological agents. This question is considered in the current chapter.
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".