Testing the face-specificity of the inversion effect in budgie experts
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
Dramatic inversion costs in the recognition and perception of faces but not objects have reinforced the view that face-specific mechanisms support holistic processing for face individuation. The alternative expertise hypothesis asserts that these effects, while appearing face-selective, reflect domain-general processing strategies for expert perceptual discrimination. Previous studies of real-world object expertise have been restricted to the context of within-class object discrimination (e.g. car model, bird and dog species), providing a weak test of the expertise hypothesis with respect to perceptual individuation. In this study, we examined a novel form of expertise in bird breeders who individuate highly homogenous birds at the identity level. Breeders of show budgies maintain aviaries of 50-300 birds with each bird being uniquely recognized based on physical characteristics such as markings and body structure. Information about each bird's relation to the social and genetic structure of the bird group is also attached to this recognition. Performance in a sequential matching task for upright and inverted birds and faces was compared across experts and novices. Results show that budgie experts outperform bird novices in the perception of upright bird images, yet this increased perceptual ability is orientation specific and is impaired for inverted bird images. These results demonstrate that inversion effects can be found for objects which are individuated and visually homogenous, and support the hypothesis that inversion costs for faces are a consequence of domain-specific experience and not necessarily due to a face-specific mechanism. Meeting abstract presented at VSS 2014
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 | 0.004 | 0.003 |
| 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 | 0.000 | 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