Limits...
On disciplinary fragmentation and scientific progress.

Balietti S, Mäs M, Helbing D - PLoS ONE (2015)

Bottom Line: Strikingly, there is no effect in the opposite causal direction.What is more, our results shows that at the heart of the mechanisms driving scientific progress we find (i) social interactions, and (ii) peer disagreement.We discuss model's implications for the design of social institutions fostering interdisciplinarity and participation in science.

View Article: PubMed Central - PubMed

Affiliation: Professorship of Computational Social Science, ETH Zurich, Switzerland.

ABSTRACT
Why are some scientific disciplines, such as sociology and psychology, more fragmented into conflicting schools of thought than other fields, such as physics and biology? Furthermore, why does high fragmentation tend to coincide with limited scientific progress? We analyzed a formal model where scientists seek to identify the correct answer to a research question. Each scientist is influenced by three forces: (i) signals received from the correct answer to the question; (ii) peer influence; and (iii) noise. We observed the emergence of different macroscopic patterns of collective exploration, and studied how the three forces affect the degree to which disciplines fall apart into divergent fragments, or so-called "schools of thought". We conducted two simulation experiments where we tested (A) whether the three forces foster or hamper progress, and (B) whether disciplinary fragmentation causally affects scientific progress and vice versa. We found that fragmentation critically limits scientific progress. Strikingly, there is no effect in the opposite causal direction. What is more, our results shows that at the heart of the mechanisms driving scientific progress we find (i) social interactions, and (ii) peer disagreement. In fact, fragmentation is increased and progress limited if the simulated scientists are open to influence only by peers with very similar views, or when within-school diversity is lost. Finally, disciplines where the scientists received strong signals from the correct answer were less fragmented and experienced faster progress. We discuss model's implications for the design of social institutions fostering interdisciplinarity and participation in science.

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Distributions of consensus shares X(10, .., 100) under different initial clustering conditions.A field with a large radius of interaction can sustain a faster consensus growth for any intermediate share of consensus. Interestingly, if the interaction radius is small and agents are initially placed in a single cluster, it is extremely hard to reach full consensus (100% consensus share) due the to reduced social influence effects on those agents that manage to leave the initial cluster. Error bars represent standard errors of the mean.[R = (0.03, 0.3), α = (0.5, 0.99), τ = 1, σ = 0.01, ε = 0.1]
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pone.0118747.g011: Distributions of consensus shares X(10, .., 100) under different initial clustering conditions.A field with a large radius of interaction can sustain a faster consensus growth for any intermediate share of consensus. Interestingly, if the interaction radius is small and agents are initially placed in a single cluster, it is extremely hard to reach full consensus (100% consensus share) due the to reduced social influence effects on those agents that manage to leave the initial cluster. Error bars represent standard errors of the mean.[R = (0.03, 0.3), α = (0.5, 0.99), τ = 1, σ = 0.01, ε = 0.1]

Mentions: Fig. 11 provides more detailed information, plotting the distribution of consensus shares over time, i.e. the time necessary to build a consensus of X% of agents within a radius of 0.05 units from the ground truth. The figure confirms the earlier findings that disciplines with a large influence radius R reach consensus faster than populations of agents with small radii. Keeping the number of initial clusters constant, a field with a larger radius of interaction can sustain a faster consensus growth for any intermediate share of consensus. In addition, even if all agents are initially placed in one single cluster away from the truth, those that are equipped with a smaller radius of interaction (see red bars) require more time to collectively find the ground-truth. Moreover, if the interaction radius is small and agents are initially placed in a single cluster, it is extremely hard to reach a perfect consensus (100% consensus share). It takes even longer than if agents are initially split up into more clusters (2 to 5). This counter-intuitive finding is obtained because noise can lead some agents to leave their initial group. With a small influence radius, these isolated agents will remain isolated until they happen to join another cluster. This, however, can last very long or may never happen when there are very few clusters initially.


On disciplinary fragmentation and scientific progress.

Balietti S, Mäs M, Helbing D - PLoS ONE (2015)

Distributions of consensus shares X(10, .., 100) under different initial clustering conditions.A field with a large radius of interaction can sustain a faster consensus growth for any intermediate share of consensus. Interestingly, if the interaction radius is small and agents are initially placed in a single cluster, it is extremely hard to reach full consensus (100% consensus share) due the to reduced social influence effects on those agents that manage to leave the initial cluster. Error bars represent standard errors of the mean.[R = (0.03, 0.3), α = (0.5, 0.99), τ = 1, σ = 0.01, ε = 0.1]
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4366147&req=5

pone.0118747.g011: Distributions of consensus shares X(10, .., 100) under different initial clustering conditions.A field with a large radius of interaction can sustain a faster consensus growth for any intermediate share of consensus. Interestingly, if the interaction radius is small and agents are initially placed in a single cluster, it is extremely hard to reach full consensus (100% consensus share) due the to reduced social influence effects on those agents that manage to leave the initial cluster. Error bars represent standard errors of the mean.[R = (0.03, 0.3), α = (0.5, 0.99), τ = 1, σ = 0.01, ε = 0.1]
Mentions: Fig. 11 provides more detailed information, plotting the distribution of consensus shares over time, i.e. the time necessary to build a consensus of X% of agents within a radius of 0.05 units from the ground truth. The figure confirms the earlier findings that disciplines with a large influence radius R reach consensus faster than populations of agents with small radii. Keeping the number of initial clusters constant, a field with a larger radius of interaction can sustain a faster consensus growth for any intermediate share of consensus. In addition, even if all agents are initially placed in one single cluster away from the truth, those that are equipped with a smaller radius of interaction (see red bars) require more time to collectively find the ground-truth. Moreover, if the interaction radius is small and agents are initially placed in a single cluster, it is extremely hard to reach a perfect consensus (100% consensus share). It takes even longer than if agents are initially split up into more clusters (2 to 5). This counter-intuitive finding is obtained because noise can lead some agents to leave their initial group. With a small influence radius, these isolated agents will remain isolated until they happen to join another cluster. This, however, can last very long or may never happen when there are very few clusters initially.

Bottom Line: Strikingly, there is no effect in the opposite causal direction.What is more, our results shows that at the heart of the mechanisms driving scientific progress we find (i) social interactions, and (ii) peer disagreement.We discuss model's implications for the design of social institutions fostering interdisciplinarity and participation in science.

View Article: PubMed Central - PubMed

Affiliation: Professorship of Computational Social Science, ETH Zurich, Switzerland.

ABSTRACT
Why are some scientific disciplines, such as sociology and psychology, more fragmented into conflicting schools of thought than other fields, such as physics and biology? Furthermore, why does high fragmentation tend to coincide with limited scientific progress? We analyzed a formal model where scientists seek to identify the correct answer to a research question. Each scientist is influenced by three forces: (i) signals received from the correct answer to the question; (ii) peer influence; and (iii) noise. We observed the emergence of different macroscopic patterns of collective exploration, and studied how the three forces affect the degree to which disciplines fall apart into divergent fragments, or so-called "schools of thought". We conducted two simulation experiments where we tested (A) whether the three forces foster or hamper progress, and (B) whether disciplinary fragmentation causally affects scientific progress and vice versa. We found that fragmentation critically limits scientific progress. Strikingly, there is no effect in the opposite causal direction. What is more, our results shows that at the heart of the mechanisms driving scientific progress we find (i) social interactions, and (ii) peer disagreement. In fact, fragmentation is increased and progress limited if the simulated scientists are open to influence only by peers with very similar views, or when within-school diversity is lost. Finally, disciplines where the scientists received strong signals from the correct answer were less fragmented and experienced faster progress. We discuss model's implications for the design of social institutions fostering interdisciplinarity and participation in science.

Show MeSH
Related in: MedlinePlus