Cognitive Psychology of Activity: Attention as a Constructive Process
Bibliographic record
Abstract
The problem of consciousness is one of the core problems in the contemporary cogni-tive science. Driven by the neuroimaging boom, most researchers look for the neural correlates or signatures of consciousness and awareness in the human brain. However, we believe that the explanatory potential of the cultural-historical activity approach to this problem is far from being exhausted. We propose Cognitive Psychology of Activity research program, or the activity theory-based constructivism as an attempt to account for multiple phenomena of human awareness and attention. This approach relies upon cultural-historical psychology and the concept of mediation by Lev S. Vygotsky, activity theory and the concept of image generation by Alexey N. Leontiev, the physiology of ac-tivity and the metaphor of movement construction by Nikolai A. Bernstein, transferred to the psychology of perception as image construction by a number of Russian researchers in 1960-es, and the understanding of attention as action by evolutionary cognitive psy-chologists of 1980-es. The central concept of our approach is a concept of task, defined by Leontiev as “a goal assigned in specific circumstances”. The goal determines choice and use of available cultural means (“mediators”) consistent with the circumstances or conditions of task performance, which in turn provide for the construction of processing units allowing for more successful (“attentive”) performance and for the awareness of visual stimuli which could otherwise be missed or ignored. The perceptual task accom-plishment is controlled at several levels organized heterarchically, with possible strategic reorganizations of this system demonstrating the constructive nature of human cognition.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.027 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".