Matthew effect

In sociology, the Matthew effect (or accumulated advantage) is the phenomenon where "the rich get richer and the poor get poorer."[1][2] In both its original and typical usage it is meant metaphorically to refer to issues of fame or status but it may also be used literally to refer to cumulative advantage of economic capital. The term was first coined by sociologist Robert K. Merton in 1968[3] and takes its name from the parable of the talents in the biblical Gospel of Matthew. As a result of the Matilda effect, Harriet Zuckerman is also credited by Merton as the co-author of the Matthew effect.[4]

Biblical origins

The concept is in two of the Parables of Jesus in the synoptic Gospels (Table 2, of the Eusebian Canons).

The concept concludes both synoptic versions of the parable of the talents:

For unto every one that hath shall be given, and he shall have abundance: but from him that hath not shall be taken even that which he hath.
— Matthew 25:29, King James Version.
For I say unto you, That unto every one which hath shall be given; and from him that hath not, even that he hath shall be taken away from him.
— Luke 19:26, King James Version.

The concept concludes two of the three synoptic versions the parable of the Lamp under a bushel (absent in the version of Matthew):

For he that hath, to him shall be given: and he that hath not, from him shall be taken even that which he hath.
— Mark 4:25, King James Version.
Take heed therefore how ye hear: for whosoever hath, to him shall be given; and whosoever hath not, from him shall be taken even that which he seemeth to have.
— Luke 8:18, King James Version.

The concept is presented again in Matthew outside of a parable during an explanation of the purpose of parables:

For whosoever hath, to him shall be given, and he shall have more abundance: but whosoever hath not, from him shall be taken away even that he hath.
— Matthew 13:12, King James Version.

The same concept is found in the noncanonical, gnostic Gospel of Thomas, saying 41.

Sociology of science

In the sociology of science, "Matthew effect" was a term coined by Robert K. Merton 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][5] 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 furthermore 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. He 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. He 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.[6]

Examples

As credit is valued in science, specific claims of the Matthew effect are contentious. Many examples below exemplify more famous scientists getting credit for discoveries due to their fame, even as other less notable scientists had preempted their work.

Ray Solomonoff [...] introduced [what is now known as] "Kolmogorov complexity" in a long journal paper in 1964. [...] This makes Solomonoff the first inventor and raises the question whether we should talk about Solomonoff complexity. [...]

In science, dramatic differences in the 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.[11]

Education

In education, the term "Matthew effect" has been adopted by psychologist Keith Stanovich to describe a phenomenon observed in research on how new readers acquire the skills to read: 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.

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.

In the words of Stanovich:

Slow reading acquisition has cognitive, behavioral, and motivational consequences that slow the development of other cognitive skills and inhibit performance on many academic tasks. In short, as reading develops, other cognitive processes linked to it track the level of reading skill. Knowledge bases that are in reciprocal relationships with reading are also inhibited from further development. The longer this developmental sequence is allowed to continue, the more generalized the deficits will become, seeping into more and more areas of cognition and behavior. Or to put it more simply – and sadly – in the words of a tearful nine-year-old, already falling frustratingly behind his peers in reading progress, "Reading affects everything you do."[12]

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.[13] "Because of preferential attachment, 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." [14] The Matthew Effect therefore explains the growth of some nodes in vast networks such as the Internet.[15]

See also

References

  1. ↑ Gladwell, Malcolm (2008-11-18). Outliers: The Story of Success (1 ed.). Little, Brown and Company. ISBN 0-316-01792-2.
  2. ↑ Shaywitz, David A. (2008-11-15). "The Elements of Success". The Wall Street Journal. Retrieved 2009-01-12.
  3. 1 2 Merton, Robert K. (1968). "The Matthew Effect in Science" (PDF). Science. 159 (3810): 56–63. doi:10.1126/science.159.3810.56. PMID 17737466.
  4. ↑ http://garfield.library.upenn.edu/merton/matthewii.pdf
  5. ↑ Merton, Robert K (1988). "The Matthew Effect in Science, II: Cumulative advantage and the symbolism of intellectual property" (PDF). ISIS. 79: 606–623. doi:10.1086/354848.
  6. ↑ Abstract of Merton's 1968 paper "The Matthew Effect in Science".
  7. ↑ Salganik, Matthew J., Peter S. Dodds, and Duncan J. Watts. (2006). Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market (PDF). Science 311 , 854–856.
  8. ↑ Sorenson, Alan T (2007). "Bestseller Lists and Product Variety" (PDF). Journal of Industrial Economics. 55: 715–738.
  9. ↑ Li, Ming; Paul Vitanyi (1997-02-27). An Introduction to Kolmogorov Complexity and Its Applications (2nd ed.). Springer. ISBN 0-387-94868-6.
  10. ↑ Petersen, Alexander M.; Jung, Woo-Sung; Yang, Jae-Suk; Stanley, H. Eugene (2011). "Quantitative and Empirical demonstration of the Matthew Effect in a study of Career Longevity". PNAS. 108 (1): 18–23. doi:10.1073/pnas.1016733108. Cite uses deprecated parameter |coauthors= (help)
  11. ↑ Serenko, A., Cox, R., Bontis, N. and Booker, L. (2011). The Superstar Phenomenon in the Knowledge Management and Intellectual Capital Academic Discipline (PDF). Journal of Informetrics 5, 333-345.
  12. ↑ Adams, Marilyn J. (1990). Beginning to Read: Thinking and Learning about Print. Cambridge, MA: MIT Press. pp. 59–60.
  13. ↑ Barabási, A-L; Albert, R (1999). "Emergence of scaling in random networks". Science. 286: 509–512. doi:10.1126/science.286.5439.509. PMID 10521342.
  14. ↑ Perc, Matjaž (2014). "The Matthew effect in empirical data". Interface. 12 (104): 20140378. doi:10.1098/rsif.2014.0378.
  15. ↑ Guadamuz, Andres (2011). Networks, Complexity And Internet Regulation - Scale-Free Law. Edward Elgar. ISBN 9781848443105.

Further reading

This article is issued from Wikipedia - version of the 10/5/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.