Bibliographic record
Abstract
Memory has been traditionally defined as a psychological capacity allowing subjects to store information "in the mind" to recover it later. This definition, supportive of a Cartesian perspective, assumes that cognition is a form of internal information processing. In recent years, the 5E paradigms (i.e., embodied, extended, enactive, embedded, ecological) have emerged as an alternative to orthodox perspectives and emphasized the constitutive role of the body and environment in cognition. By defining cognition as adaptive behavior, these paradigms have questioned the scope of certain basic concepts in the cognitive sciences, such as "agency", "meaning", and "mental representation." In this presentation, I will introduce an ecological-enactive model of memory based on the Material Engagement Theory (Prezioso & Alessandroni, 2022; see also Malafouris & Koukouti, 2018) and discuss its implications for psychological research. Specifically, I will defend: (i) that "memory" does not refer to an internal capacity but to a type of activity that subjects carry out when they interact in and with the world; (ii) that "remembering" does not occur thanks to the encoding, storage, and retrieval of mental content but to the update of specific forms of interaction with material culture; and (iii) that objects (e.g., a cup or a spoon) are full-fledged cognitive agents because they prompt us to re-instantiate forms of material engagement previously experienced. Considering these three points, I will highlight the urgent need to conduct studies considering the cognitive ecologies wherein subjects remember. Finally, I will address the relationship between the proposed model and other contemporary contributions on the development of conceptual thinking and intentional understanding (Alessandroni, 2021, 2023; Vietri et al., 2022).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".