↓ Skip to main content

Skill learning and the evolution of social learning mechanisms

Overview of attention for article published in BMC Ecology and Evolution, August 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

blogs
1 blog
twitter
8 X users
reddit
1 Redditor

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
65 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Skill learning and the evolution of social learning mechanisms
Published in
BMC Ecology and Evolution, August 2016
DOI 10.1186/s12862-016-0742-9
Pubmed ID
Authors

Daniel J. van der Post, Mathias Franz, Kevin N. Laland

Abstract

Social learning is potentially advantageous, but evolutionary theory predicts that (i) its benefits may be self-limiting because social learning can lead to information parasitism, and (ii) these limitations can be mitigated via forms of selective copying. However, these findings arise from a functional approach in which learning mechanisms are not specified, and which assumes that social learning avoids the costs of asocial learning but does not produce information about the environment. Whether these findings generalize to all kinds of social learning remains to be established. Using a detailed multi-scale evolutionary model, we investigate the payoffs and information production processes of specific social learning mechanisms (including local enhancement, stimulus enhancement and observational learning) and their evolutionary consequences in the context of skill learning in foraging groups. We find that local enhancement does not benefit foraging success, but could evolve as a side-effect of grouping. In contrast, stimulus enhancement and observational learning can be beneficial across a wide range of environmental conditions because they generate opportunities for new learning outcomes. In contrast to much existing theory, we find that the functional outcomes of social learning are mechanism specific. Social learning nearly always produces information about the environment, and does not always avoid the costs of asocial learning or support information parasitism. Our study supports work emphasizing the value of incorporating mechanistic detail in functional analyses.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 5%
Senegal 1 2%
Unknown 61 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 29%
Student > Master 12 18%
Researcher 6 9%
Student > Bachelor 4 6%
Student > Doctoral Student 4 6%
Other 11 17%
Unknown 9 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 35%
Psychology 18 28%
Social Sciences 3 5%
Neuroscience 3 5%
Nursing and Health Professions 2 3%
Other 6 9%
Unknown 10 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 September 2016.
All research outputs
#3,105,286
of 25,374,647 outputs
Outputs from BMC Ecology and Evolution
#820
of 3,714 outputs
Outputs of similar age
#51,254
of 352,659 outputs
Outputs of similar age from BMC Ecology and Evolution
#22
of 69 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 352,659 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.