Cause and Effect Theories of Attention: The Role of Conceptual Metaphors
Why this work is in the frame
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Bibliographic record
Abstract
Scientific concepts are defined by metaphors. These metaphors determine what attention is and what count as adequate explanations of the phenomenon. The authors analyze these metaphors within 3 types of attention theories: (a) “cause” theories, in which attention is presumed to modulate information processing (e.g., attention as a spotlight; attention as a limited resource); (b) “effect” theories, in which attention is considered to be a by-product of information processing (e.g., the competition metaphor); and (c) hybrid theories that combine cause and effect aspects (e.g., biased-competition models). The present analysis reveals the crucial role of metaphors in cognitive psychology, neuroscience, and the efforts of scientists to find a resolution to the classic problem of cause versus effect interpretations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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