Bibliographic record
Abstract
Some species are social in that they live in groups, but the animals within the groups are not friendly with each other. This chapter will deal with three categories which include species of this nature: primates, large herbivores, and meerkats. Primates Primates considered in this chapter are squirrel monkeys, colobine monkeys, patas monkeys, hamadryas baboons, and sifaka lemurs. Some theorists postulate that the evolution of friendships among female primates depends, to a large extent, upon the environment, especially the food they eat, as we shall see in the discussion of squirrel monkeys. Lynne Isbell and Truman Young (2002) hypothesize on the significance of food and other factors in the life of primates: Accessibility of food: In species that eat high-quality food growing in clumps, females should be philopatric (remain in their natal area for life) and defend the food source aggressively against members of other groups. In areas with food uniformly distributed or in small high-quality clumps, the females should emigrate at puberty, lack dominance hierarchies, and not quarrel with other groups given that their food source is not really defensible. Dominance hierarchy: Food that is spread out and largely indefensible can still be problematic. There can be scramble competition for it, meaning that the individuals who get to it first will reduce it for others by eating it themselves, and contest competition whereby high-ranking individuals showing aggression can gain preferential access to the food. Relationships: If females in a group are closely related, they should support each other (nepotism) in order to increase the number of their joint progeny. Possibility of infanticide: If members of a species sometimes kill the offspring of females, then these females should bond together to try to prevent this catastrophe. Heavy predation: If a species is subject to intense predation, the females might band together to counter-attack (depending on the size of the predator) and/or prefer to stay close together to try to detect the danger and evade it. In contrast to this environmental theory for female behavior, male behavior is largely driven by their instinctual wish to be near females, so that they can detect those who are in estrus and mate with as many of them as are willing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.012 |
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".