paper rejection cycle

paper_rejection_cycle.R

library(tidyverse)

n_papers <- 1000
papers <- tibble(
  paper = 1:n_papers,
  quality = rnorm(n_papers),
  reviews = 0,
  published = FALSE,
  journal = NA_real_,
  most_recent_assessment = NA_real_
)

n_journals <- 20
journals <- tibble(
  journal = 1:n_journals,
  threshold = rnorm(n_journals),
  fame = 0.5*threshold + 0.5 * rnorm(n_journals)
) %>% arrange(desc(fame))

for(p in seq_along(1:n_papers)) {
  for(j in seq_along(1:n_journals)) {
    papers[p, "most_recent_assessment"] <- 0.3*papers[p, "quality"] + rnorm(1)
    papers[p, "reviews"] <- papers[p, "reviews"] + 3
    if(papers[p, "most_recent_assessment"] > journals[j, "threshold"]) {
      papers[p, "published"] <- TRUE
      papers[p, "journal"] <- journals[j, "journal"]
      break
    }
  }
}

papers_in_journals <- papers %>% left_join(journals)
papers_in_journals %>% select(quality, fame, reviews) %>% cor(use = 'pairwise')
qplot(fame, reviews, data= papers_in_journals)