The Matthew effect, sometimes called the Matthew principle, is the tendency of individuals to accrue social or economic success in proportion to their initial level of popularity, friends, and wealth. It is sometimes summarized by the adage or platitude "the rich get richer and the poor get poorer".[1][2] Also termed the "Matthew effect of accumulated advantage", taking its name from the Parable of the Talents in the biblical Gospel of Matthew, it was coined by sociologists Robert K. Merton and Harriet Zuckerman in 1968.[3][4]
The Matthew effect may largely be explained by preferential attachment, whereby wealth or credit is distributed among individuals according to how much they already have. This has the net effect of making it increasingly difficult for low ranked individuals to increase their totals because they have fewer resources to risk over time, and increasingly easy for high rank individuals to preserve a large total because they have a large amount to risk.[5] Early studies of Matthew effects were primarily concerned with the inequality in the way scientists were recognized for their work. However, Norman W. Storer, of Columbia University, led a new wave of research. He believed he discovered that the inequality that existed in the social sciences also existed in other institutions.[6]
The concept is presented again in Matthew outside of a parable during Christ's explanation to his disciples of the purpose of parables:
And he answered them, "To you it has been given to know the secrets of the kingdom of heaven, but to them it has not been given. For to him who has will more be given, and he will have abundance; but from him who has not, even what he has will be taken away."
In the sociology of science, "Matthew effect" was a term coined by Robert K. Merton and Harriet Anne Zuckerman to describe how, among other things, eminent scientists will often get more credit than a comparatively unknown researcher, even if their work is similar; it also means that credit will usually be given to researchers who are already famous.[3][4] For example, a prize will almost always be awarded to the most senior researcher involved in a project, even if all the work was done by a graduate student. This was later formulated by Stephen Stigler as Stigler's law of eponymy– "No scientific discovery is named after its original discoverer"– with Stigler explicitly naming Merton as the true discoverer, making his "law" an example of itself. Merton and Zuckerman further argued that in the scientific community the Matthew effect reaches beyond simple reputation to influence the wider communication system, playing a part in social selection processes and resulting in a concentration of resources and talent. They gave as an example the disproportionate visibility given to articles from acknowledged authors, at the expense of equally valid or superior articles written by unknown authors. They also noted that the concentration of attention on eminent individuals can lead to an increase in their self-assurance, pushing them to perform research in important but risky problem areas.[3]
Examples
Experiments manipulating download counts or bestseller lists for books and music have shown consumer activity follows the apparent popularity.[7][8][9]
A model for career progress quantitatively incorporates the Matthew Effect in order to predict the distribution of individual career length in competitive professions. The model predictions are validated by analyzing the empirical distributions of career length for careers in science and professional sports (e.g. Major League Baseball).[10] As a result, the disparity between the large number of short careers and the relatively small number of extremely long careers can be explained by the "rich-get-richer" mechanism, which in this framework, provides more experienced and more reputable individuals with a competitive advantage in obtaining new career opportunities.
A large Matthew effect was discovered in a study of science funding in the Netherlands, where winners just above the funding threshold were found to accumulate more than twice as much funding during the subsequent eight years as non-winners with near-identical review scores that fell just below the threshold.[11]
In science, dramatic differences in productivity may be explained by three phenomena: sacred spark, cumulative advantage, and search costs minimization by journal editors. The sacred spark paradigm suggests that scientists differ in their initial abilities, talent, skills, persistence, work habits, etc. that provide particular individuals with an early advantage. These factors have a multiplicative effect which helps these scholars succeed later. The cumulative advantage model argues that an initial success helps a researcher gain access to resources (e.g., teaching release, best graduate students, funding, facilities, etc.), which in turn results in further success. Search costs minimization by journal editors takes place when editors try to save time and effort by consciously or subconsciously selecting articles from well-known scholars. Whereas the exact mechanism underlying these phenomena is yet unknown, it is documented that a minority of all academics produce the most research output and attract the most citations.[12]
Education
In education, the term "Matthew effect" has been adopted by psychologist Keith Stanovich[13] and popularised by education theorist Anthony Kelly to describe a phenomenon observed in research on how new readers acquire the skills to read. Effectively, early success in acquiring reading skills usually leads to later successes in reading as the learner grows, while failing to learn to read before the third or fourth year of schooling may be indicative of lifelong problems in learning new skills.[14]
This is because children who fall behind in reading would read less, increasing the gap between them and their peers. Later, when students need to "read to learn" (where before they were learning to read), their reading difficulty creates difficulty in most other subjects. In this way they fall further and further behind in school, dropping out at a much higher rate than their peers.[15] This effect has been used in legal cases, such as Brody v. Dare County Board of Education.[16] Such cases argue that early education intervention is essential for disabled children, and that failing to do so negatively impacts those children.[17]
A 2014 review of Matthew effect in education found mixed empirical evidence, where Matthew effect tends to describe the development of primary school skills, while a compensatory pattern was found for skills with ceiling effects.[18] A 2016 study on reading comprehension assessments for 99 thousand students found a pattern of stable differences, with some narrowing of the gap for students with learning disabilities.[19]
Network science
In network science, the Matthew effect is used to describe the preferential attachment of earlier nodes in a network, which explains that these nodes tend to attract more links early on.[20] Due to preferential attachment, Matjaž Perc writes "a node that acquires more connections than another one will increase its connectivity at a higher rate, and thus an initial difference in the connectivity between two nodes will increase further as the network grows, while the degree of individual nodes will grow proportional with the square root of time."[5] The Matthew Effect therefore explains the growth of some nodes in vast networks such as the Internet.[21]
Markets with social influence
Social influence often induces a rich-get-richer phenomenon where popular products tend to become even more popular.[22] An example of the Matthew Effect's role on social influence is an experiment by Salganik, Dodds, and Watts in which they created an experimental virtual market named MUSICLAB. In MUSICLAB, people could listen to music and choose to download the songs they enjoyed the most. The song choices were unknown songs produced by unknown bands. There were two groups tested; one group was given zero additional information on the songs and one group was told the popularity of each song and the number of times it had previously been downloaded.[23] As a result, the group that saw which songs were the most popular and were downloaded the most were then biased to choose those songs as well. The songs that were most popular and downloaded the most stayed at the top of the list and consistently received the most plays. To summarize the experiment's findings, the performance rankings had the largest effect boosting expected downloads the most. Download rankings had a decent effect; however, not as impactful as the performance rankings.[24] Abeliuk et al. (2016) also proved that when utilizing "performance rankings", a monopoly will be created for the most popular songs.[25]
↑ Rigney, Daniel (2010). "Matthew Effects in the Economy.” The Matthew Effect: How Advantage Begets Further Advantage. Columbia University Press. pp. pp. 35–52.
↑ Stanovich, Keith E. (1986). "Matthew Effects in Reading: Some Consequences of Individual Differences in the Acquisition of Literacy". Reading Research Quarterly. 21: 360–407. doi:10.1177/0022057409189001-204.
↑ Kempe, C., Eriksson-Gustavsson, A. L., & Samuelsson, S (2011). "Are There any Matthew Effects in Literacy and Cognitive Development?". Scandinavian Journal of Educational Research. 55 (2): 181–196. doi:10.1080/00313831.2011.554699. S2CID145163197.{{cite journal}}: CS1 maint: multiple names: authors list (link)
↑ Adams, Marilyn J. (1990). Beginning to Read: Thinking and Learning about Print. Cambridge, MA: MIT Press. pp. 59–60.
↑ Pfost, Maximilian; Hattie, John; Dörfler, Tobias; Artelt, Cordula (2014). "Individual Differences in Reading Development: A Review of 25 Years of Empirical Research on Matthew Effects in Reading". Review of Educational Research. 84 (2): 203–244. doi:10.3102/0034654313509492. ISSN0034-6543.
Bahr, Peter Riley (2007). "Double jeopardy: Testing the effects of multiple basic skill deficiencies on successful remediation". Research in Higher Education. 48 (6): 695–725. doi:10.1007/s11162-006-9047-y. S2CID144937969.
Cunningham, A. E., & Chen, Y.–J. (2014). Rich-get-richer effect (Matthew Effects). In P. Brooks & V. Kempe (Eds.), Encyclopedia of Language Development. New York: Sage.
Rigney, Daniel (2010). The Matthew Effect: How Advantage Begets Further Advantage. Columbia University Press.
Stanovich, Keith E. (2000). Progress in Understanding Reading: Scientific Foundations and New Frontiers. New York: Guilford Press.nningham, A. E., & Chen, Y.–J. (2014). Rich-get-richer effect (Matthew Effects). In P. Brooks & V. Kempe (Eds.), Encyclopedia of Language Development. New York: Sage.
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