Inversion Effect of Hand Postures: Effect of Visual Experience Over Long and Short Term
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
Some researchers argue that holistic processing is unique to face recognition supported by the face inversion effect. However, findings such as the body inversion effect challenge the face processing-specificity hypothesis, thus supporting the expertise hypothesis. Few studies have explored a possible hand inversion effect which could involve special processing similar to the face and body. We conducted four experiments to investigate the time course and flexibility of the hand posture inversion effect. We utilized a same/different discrimination task (Experiments 1 and 2), an identification task (Experiment 3), and a training paradigm involving the exposure of different hand orientations (Experiment 4). The results show the hand posture inversion effect (with fingers up as upright orientation) was not initially observed during the early phase of testing, but occurred in later phases. This suggests that both lifetime experience and recent exposure affect the hand posture inversion effect. We also found the hand posture inversion effect, once established, was stable across days and remained consistent across different tasks. In addition, the hand posture inversion effect for specific orientations could be obtained with short-term training of a given orientation, indicating the cognitive process is flexible.
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 | 0.000 | 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) | 0.001 | 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