Separating Responses Based on Demand Characteristics and Phenomenological–Spatial Associations
Bibliographic record
Abstract
Previous researchers have found that participants associate higher frequencies with locations that are higher in space and lower frequencies with lower locations, creating a phenomenological-spatial association for the frequency of auditory tones. With such an association, the frequency of an auditory tone could potentially bias movements along multiple axes. This hypothesis was tested. In four experiments, nine frequencies (250-1,250 Hz) were binaurally presented to blindfolded participants (n = 10, 12, 20, & 9; M age = 22 yr.) who indicated the perceived location of the stimuli on a measurement scale oriented in the vertical, the horizontal (Experiment 1), or depth dimension (Experiment 2). In Experiment 3, participants were asked to indicate the perceived location of the frequencies on a two-dimensional vertical board located in front of them. In Experiment 4, participants indicated the perceived location in three-dimensional space. An optoelectronic device recorded at all locations. Analyses of constant error indicated a spatial association in the vertical, horizontal, and depth dimensions when responses were restricted to only one dimension (Experiments 1 & 2). Higher frequencies were perceived to be located higher, farther to the right, and farther away from the body than lower frequencies. However, this spatial association was only exhibited in the vertical dimension when the responses were unconstrained in two dimensions (vertical and horizontal; Experiment 3) and all three dimensions (Experiment 4). Although this spatial association is a robust phenomenon, it appears that the association only biases actions when indicating perceived locations in the vertical dimension during unconstrained responses.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".