scholarly journals The role of the tolerance-fecundity trade-off in maintaining intraspecific seed trait variation in a widespread dimorphic herb

Plant Biology ◽  
2012 ◽  
Vol 15 (5) ◽  
pp. 899-909 ◽  
Author(s):  
J. Villellas ◽  
M. B. García
Keyword(s):  
2019 ◽  
Vol 56 (3) ◽  
pp. 361-378 ◽  
Author(s):  
Andreas Lanz ◽  
Jacob Goldenberg ◽  
Daniel Shapira ◽  
Florian Stahl

This article addresses seeding policies in user-generated content networks by challenging the role of influencers in a setting of unpaid endorsements. On such platforms, the content is generated by individuals and firms interested in self-promotion. The authors use data from a worldwide leading music platform to study unknown music creators who aim to increase exposure of their content by expanding their follower base through directing outbound activities to other users. The authors find that the responsiveness of seeding targets strongly declines with status difference; thus, unknown music creators (the majority) do not generally benefit at all from seeding influencers. Instead, they should gradually build their status by targeting low-status users rather than attempt to “jump” by targeting high-status ones. This research extends the seeding literature by introducing the concept of risk to dissemination dynamics in online communications, showing that unknown music creators do not seed specific status levels but rather choose a portfolio of seeding targets while solving a risk versus return trade-off. The authors discuss various managerial implications for optimal seeding in user-generated content networks.


Urban Studies ◽  
2021 ◽  
pp. 004209802199178
Author(s):  
Nan Liu

In housing markets there is a trade-off between selling time and selling price, with pricing strategy being the balancing act between the two. Motivated by the Home Report scheme in Scotland, this paper investigates the role of information symmetry played in such a trade-off. Empirically, this study tests if sellers’ pricing strategy changes when more information becomes available and whether this, in turn, affects the trade-off between the selling price and selling time. Using housing transaction data of North-East Scotland between 1998Q2 and 2018Q2, the findings show that asking price has converged to the predicted price of the property since the introduction of the Home Report. While information transparency reduces the effect of ‘overpricing’ on selling time, there is little evidence to show that it reduces the impact of pricing strategy on the final selling price in the sealed-bid context.


2004 ◽  
Vol 46 (4) ◽  
pp. 491-497 ◽  
Author(s):  
A.F.H. Ros ◽  
R. Bruintjes ◽  
R.S. Santos ◽  
A.V.M. Canario ◽  
R.F. Oliveira

1996 ◽  
Vol 28 (1) ◽  
pp. 55-70
Author(s):  
Gregory Schraw

Three experiments examined the trade-off between the text-based and task-based importance. Text-based importance was defined as information in a text that is important due to its structural relation to other text segments. Task-based importance was defined as text information that is important due to external constraints such as instructions. Undergraduates in this study spontaneously adopted an interactive, compensatory strategy in which task-based importance superseded the role of text-based importance. Implications for reading instruction and practice were discussed.


2016 ◽  
Author(s):  
Anna C. Schapiro ◽  
Nicholas B. Turk-Browne ◽  
Matthew M. Botvinick ◽  
Kenneth A. Norman

AbstractA growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippocampus specializes in memorizing individual episodes. In particular, the Complementary Learning Systems theory argues that there is a computational trade-off between learning the specifics of individual experiences and regularities that hold across those experiences. We asked whether it is possible for the hippocampus to handle both statistical learning and memorization of individual episodes. We exposed a neural network model that instantiates known properties of hippocampal projections and subfields to sequences of items with temporal regularities. We found that the monosynaptic pathway — the pathway connecting entorhinal cortex directly to region CA1 — was able to support statistical learning, while the trisynaptic pathway — connecting entorhinal cortex to CA1 through dentate gyrus and CA3 — learned only individual episodes, with apparent representations of regularities resulting from associative reactivation through recurrence. Thus, in paradigms involving rapid learning, the computational trade-off between learning episodes and regularities may be handled by separate anatomical pathways within the hippocampus itself.


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