6.2 KiB
| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Matthew effect | 3/4 | https://en.wikipedia.org/wiki/Matthew_effect | reference | science, encyclopedia | 2026-05-05T13:49:17.863984+00:00 | kb-cron |
== Career progression == 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). 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. Bask (2024) reviewed theoretical research on academic career progression and found that Feichtinger et al. developed a model where a researcher's reputation grows through scientific effort but declines without continual activity Their model incorporates the Matthew effect, in that researchers with high initial reputations benefit more from their efforts, while those with low reputations may see theirs diminish even with similar effort. They showed that if a researcher starts with low reputation, their career is likely to decline and eventually end, whereas researchers starting with high reputation may either sustain a successful career or face early exit depending on their effort over time.
== Markets with social influence == Experiments manipulating download counts or bestseller lists for books and music have shown consumer activity follows the apparent popularity. Social influence often induces a rich-get-richer phenomenon where popular products tend to become even more popular. 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. 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. Abeliuk et al. (2016) also proved that when utilizing "performance rankings", a monopoly will be created for the most popular songs.
== Cumulative inequality theory ==
The ideas of this theory were developed by Kenneth Ferraro and colleagues as an integrative or middle-range theory. Originally specified in five axioms and nineteen propositions, cumulative inequality theory incorporates elements from the following theories and perspectives, several of which are related to the study of society:
Robert Merton articulated the Matthew effect to explain accumulating advantage Glen Elder's life course perspective Stress process theory Age stratification theory Ferraro and Shippee (2009) further developed this framework, asserting that "social systems generate inequality, which is manifested over the life course via demographic and developmental processes." McDonough et al. (2015) studied cumulative disadvantage in the generations of health inequality among mothers in Britain and the United States. The study examined if "adverse circumstances early in the life course cumulate as health harming biographical patterns across working and family caregiving years." Also, it was examined if institutional context moderated cumulative effects of micro level processes. The results showed that existing health disparities of women in midlife, during work and family rearing time, were intensified by cumulative disadvantages caused by adversities in early life. McLean (2010) studied U.S. combat and non-combat veterans through the lens of cumulative disadvantage. He found that negative outcomes caused by disability and unemployment were more likely to influence the lives of combat veterans, who often suffered physical and emotional trauma that impeded their ability to obtain employment. Woolredge et al. (2015) studied prison sentencing across racial groups, specifically focusing on African American males with prior felony convictions. They examined how pre-trial processes affect trial outcomes, determining that cumulative disadvantage existed for African American males and young men. The effect was observed in bond amounts, pre-trial detention, and the likelihood of prison sentences; however, no significant effect was found regarding charge reductions or sentence length. Ferraro & Moore (2003) applied the theory to the long-term consequences of early obesity on midlife health and socioeconomic attainment. The study shows that obesity experienced in early life leads to lower-body disability, and increased health risk factors. The research also connects early-life obesity to social stigma and found that it negatively impacts labor market positioning and wages. Crystal et al. (2016) used the Gini coefficient to analyze how cumulative advantage influenced economic inequality within age cohorts between 1980 and 2010. The study found that inequality was highest among individuals aged 65 and older, with significant increases observed during economic recessions, times of war, and among the baby boomer generation. The researchers utilized these patterns to estimate how potential changes to Social Security might impact older adults in the United States. Cumulative inequality and cumulative disadvantage theories provide a framework for examining how various social and demographic factors intersect over time to influence public policy and individual roles within society.