| Abstract: |
Does scientific publishing reward the quality of ideas or the advantage of
connections? The question is universal to prestige-driven science, yet it has
resisted decades of study because a paper's quality could not be gauged ahead
of its publication fate without using that fate as the yardstick. We break
this constraint by measuring a paper's idea quality directly from its text,
before publication, using a discipline-trained LLM evaluator that scores the
idea without seeing author names or outcomes. Using economics as a case study,
we combine this text-legible idea-quality score with an execution-quality
rubric, a connection index, an author-ability index, and an off-the-shelf
language-model text score to estimate a five-input production function for
journal placement across 6, 208 economics working papers. The inputs are not
rivals but a sequence along the ladder of prestige. Execution sets a
meritocratic floor and is the largest input overall. Text-legible idea quality
grades the rungs in between. Connections set a favoritism ceiling that bites
mainly near the apex, the most selective journals. Connections work through
two additive channels: connected authors write papers that score higher, and
at equal scores their papers are still more likely to place better. Yet this
advantage is bounded. Connections raise the odds of every rung without making
the apex the typical outcome for ordinary ideas, and even the highest-scoring
papers face real friction reaching the visible journal ladder. The result
nests, rather than chooses between, the meritocracy and network accounts of
how science is published. |