Merit or networks? What decides where research is published
2026-06-02 • Artificial Intelligence
Artificial Intelligence
AI summaryⓘ
The authors studied how scientific papers in economics get published, asking whether ideas or connections matter more. They created a way to measure the quality of a paper's ideas from the text before publication, without bias from authors or outcomes. They found that good execution is the main factor, idea quality matters too, and connections mostly help at the top journals but don't guarantee success. Their work shows that both merit and networking play roles in getting published, with neither fully dominating.
scientific publishingidea qualityexecution qualityacademic networksjournal placementeconomics researchprestigelanguage modelsmeritocracyfavoritism
Authors
Ning Li
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.