Social motivation: attachment and altruism
Bibliographic record
Abstract
ATTACHMENT ACTIVITIES Motivational influences that are specifically social constitute the subject of this chapter. Social motives involve activities that affect interactions among organisms of the same species as well as organisms of other species. I will deal with only two issues in this short chapter: the formation and maintenance of social bonds between individuals; and that of pro-social and altruistic acts. The functional and proximate causal aspects of these phenomena will be considered in the analysis. The first and foremost social motive concerns the formation of the bond between an infant and its primary caretaker, usually the mother. The material in Chapter 3 deals with this issue from the perspective of the mother, whilst the material in this chapter complements it through an analysis of processes in the infant. The attachment of a human infant to its caretaker has biological roots. Both babies and adults are programmed by evolution to become attached in certain ways because the former is dependent upon the latter for survival. Attachment behaviours refer to a broad classification of behaviours that keep the infant in close proximity to an attachment figure. These behaviours include crying, clinging and approaching, as well as others produced when the infant is separated from the attachment figure. Mammals live in a diverse array of habitats and social structures. The basic unit of the family is the mother and infant. However, our examination of material in Chapter 3 suggests that other conspecifics may be involved to some exent in infant caregiving. These caregivers can include the father, siblings or peers, or combinations of these conspecifics.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".