Recalibration of the relationship between visual and action space: Evidence for generalization across actions
Bibliographic record
Abstract
In a blind walking task, participants can be induced to under or overestimate the distances to visual targets by training them with mismatching viewed and walked distances (Ellard & Thompson, VSS 2002). This may indicate that participants have recalibrated the relationship between visual space and action space, or it might mean that they have learned a series of associations between the appearance of a target and the effort required to walk to it. In order to distinguish between these possibilities, we conducted new studies in which we trained participants using mismatched visual and walked target locations, and then tested them by asking them to either throw a ball at a visual target or to complete a spatial updating task. In both cases, the training consisted of 21 blindwalking trials at distances ranging from 8 to 16 m. On each trial, the participant was asked to view the target and then, while blindfolded, they were led to a location that they were told corresponded to the visual target location. In conflict conditions, the walked location was either 20% closer (−20 condition) or 20% further away (+20 condition) than the visual target location. Following training, some participants were required to throw a ball at a visual target. Other participants were presented with a spatial updating task in which they were asked to briefly view an offset visual target, walk forward without vision until told to stop, and then turn to face the target Results from both the ball throwing and the updating task showed that the conflict training exerted an effect on responses in the predicted directions, but the −20 condition exerted a much stronger effect than the +20 condition. These findings provide preliminiary evidence that our training procedure recalibrated the relationship between visual space and action space.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".