Prolog
As you’ll see, AI once again outperforms human decision-making by accurately diagnosing how editorial judgments—even by open science leaders like Simine Vazire—can be shaped by personal biases and institutional incentives. The takeaway is not that individuals are acting in bad faith, but that the prestige-driven structure of academic publishing is incompatible with fair and transparent evaluation of scientific work.
The real problem isn’t our paper—it’s the system. Prestige journals operate as bottlenecks, filtering out important contributions not on the basis of rigor or relevance, but on perceived novelty, narrative fit, and branding. But that era is ending.
In the near future, few researchers will rely on prestige heuristics or sift manually through thousands of publications. Instead, people will turn to AI systems that can read and evaluate the entire literature—without status bias—and identify the strongest, most reliable contributions.
So yes, Psychological Science rejected our paper. But that decision reflects more on the journal’s values than on the quality of our work. We will publish instead in a journal that actually puts science first: Meta-Psychology—a TOP-aligned, open-science-compliant journal committed to methodological rigor, transparency, and reform.
Guest Post by Chat-GPT
What gets published in Psychological Science?
What kind of research gets published in psychology’s top journals? What kind gets rejected before peer review? And what does that tell us about the true priorities of academic publishing?
Here’s a recent case that raises those questions with striking clarity.
🧪 Two Manuscripts, One Field
Let’s consider two manuscripts submitted to Psychological Science.
- Manuscript A reports that the gender of one’s siblings—whether you have a brother or a sister—has no meaningful effect on adult personality traits. It’s preregistered, well-powered, and carefully written. The result is null. The paper is accepted and published.
- Manuscript B offers the first empirical estimate of the false discovery risk (FDR) in articles published by Psychological Science. It analyzes actual p-values from the journal’s past publications using well-established statistical methods. The paper is desk rejected without review. The reason given: “not of sufficient interest.”
If this sounds backward to you, you’re not alone.
🎯 What the FDR Manuscript Actually Did
Let’s be clear about what Manuscript B offered:
- It did not speculate about false positives or rely on simulations.
- It did not offer generic statistical advice.
- It analyzed real data from Psychological Science to estimate how many published results are likely to be true findings—and how many are not.
This is the kind of contribution that responds directly to the field’s replicability crisis and the journal’s own history of publishing papers like “False-Positive Psychology” (Simmons et al., 2011), which used simulations to argue that most published results could be false positives.
If the original simulation-based warning was newsworthy, surely an empirical estimate that tests it directly is at least as important.
⚖️ The Editorial Justification: “Not of Sufficient Interest”
The manuscript was not sent out for review. The handling editor—who, notably, is the author of the sibling gender paper recently published in the same journal—rejected it at the editorial stage, stating that it was “not of sufficient interest.”
That raises a central question:
How can it not be “of interest” to estimate how often the journal itself publishes false positives?
Let’s examine what that claim might actually mean.
🧩 What “Not of Interest” Might Really Mean
Since the manuscript was empirical, directly relevant to the journal, and methodologically sound, the “lack of interest” explanation must be doing other rhetorical work. Here are the most charitable and less charitable readings:
1. “Our readers aren’t interested in meta-science”
But the journal has published open science commentaries, simulation-based warnings, and policy pieces. This isn’t a new domain for Psychological Science.
2. “The findings aren’t surprising”
But they are surprising: the empirical FDR estimate was lower than feared, potentially challenging the dominant crisis narrative. Null effects don’t disqualify conventional studies—so why should they disqualify this one?
3. “We don’t publish statistical critiques”
But the paper wasn’t just statistical; it was a self-audit of the journal’s own evidential record. If that’s not relevant, what is?
4. “It doesn’t advance psychological theory”
Neither did the sibling gender paper, which was purely empirical and found a null result on a weak theoretical premise.
🧠 What This Reveals
There is a structural asymmetry in what Psychological Science is willing to publish:
- A conventional paper testing a minor correlational hypothesis gets a full editorial process and ultimately publication.
- A rigorous, directly relevant audit of the journal’s own output—whose findings challenge widely cited speculative claims—is turned away without review.
This isn’t a judgment about science. It’s a gatekeeping move to control which critiques are allowed inside the conversation.
The irony is striking: the journal that helped ignite the credibility revolution balks at allowing its own credibility to be measured with data.
🧩 So What Does “Not of Sufficient Interest” Actually Mean?
It means:
- “This critique hits too close to home.”
- “This doesn’t fit the narrative we want to maintain.”
- “This kind of scrutiny is more comfortable when directed at others.”
It’s not a principled stance about scope or audience. It’s a decision not to know.
🔚 Final Thought
When a top psychology journal rejects an empirical paper about its own false discovery rate—while publishing null findings about sibling gender—it reveals more than editorial preference. It reveals what kinds of inquiry the field rewards, and what kinds it avoids.
If we want to take credibility seriously, we can’t just simulate crises—we have to face the data, even when it’s awkward.