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Record W306848735 · doi:10.18174/177368

Personality in a group living species : social information, collective movements and social decision-making

2011· dissertation· en· W306848735 on OpenAlexfundno aff
Ralf H. J. M. Kurvers

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersWageningen University and ResearchNatural Sciences and Engineering Research Council of CanadaKoninklijke Nederlandse Akademie van Wetenschappen
KeywordsBoldnessPersonalitySocial psychologyBig Five personality traitsCognitive psychologyForagingPsychologyContext (archaeology)EcologyBiology

Abstract

fetched live from OpenAlex

movements.Leadership is the initiation of new directions of locomotion by one or more individuals, which are then followed by other group members (Krause et al. 2000). Social information useOne of the benefits of living in groups is that an individual has access to social information.Individuals might use two forms of information, either personal information, usually retrieved on a trial and error basis by interacting with the physical environment, or they might use information made available by other individuals, known as social information (Danchin et al. 2004;Dall et al. 2005).Social information use has been studied extensively in a wide variety of species and in many different contexts (Galef & Giraldeau 2001;Valone & Templeton 2002;Danchin et al. 2004;Valone 2007).Individuals use social information to decide with whom to mate (mate choice copying, Nordell & Valone 1998;Valone & Templeton 2002), where to breed (habitat copying, Danchin et al. 1998), where to forage (Drent & Swierstra 1977; Coolen et al. 2003), when to leave a food patch (Templeton & Giraldeau 1995, 1996), what food to eat (Galef 1990) and when to flee from a predator (Chivers & Smith 1998).Social information use indeed affects various important aspects of an individual's ecology, such as foraging, dispersal and space use (Seppänen et al. 2007).Despite a rich tradition of studies on social information use the relationship between animal personality and social information use is poorly studied.In this thesis I studied whether variation in personality traits is correlated with variation in the use of social information.That the value of social information might be different for 2 individuals in a group can be illustrated by a simple example.Consider a group of 3 individuals with individual a dominant over b and c, and individual b dominant over c.If individual b finds a food patch which can be monopolized this information is valuable for individual a, as it can displace individual b and take over the food patch.However, for individual c the exact same information is not valuable since it cannot use the information as it can not displace individual b and access the food.This illustrates that within a group of individuals the value of social information might differ between individuals.Despite this obvious example, there are few studies which take an individual approach to social information use and generally it is assumed that social information is equally valuable to each individual in a population and consequently most studies focus on the conditions under which an animal is expected to use social information (Galef & Giraldeau 2001;Danchin et al. 2004;Kendal et al. 2005;Valone 2007).In this thesis I studied the relationship between social information use and personality in several different contexts to test if variation in personality reflects differences in the use of social information.Maintenance of variation One of the major challenges in animal personality is to explain the evolution and maintenance of animal personality.Several (non-mutually exclusive) mechanisms have been suggested, including spatiotemporal variation in environmental conditions (Sih et al. 2003;Dall et al. 2004;Dingemanse et al. 2004;Smith & Blumstein 2008;Réale et al. 2010), differences in life-history trade-offs (Wolf et al. 2007;Gyuris et al. 2010; see also Biro & Stamps 2008;Réale et al. 2009) and sexual selection (Schuett et al. 2010).A fourth mechanism is negative frequency dependent selection (Wolf et al. 2008).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.258
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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