Agent Skills
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eursr-review-process
GitHub解析欧洲社会学评论(ESR)的双盲同行评审流程，涵盖编辑筛选、外部专家评审及决策类别。指导作者应对匿名性要求、量化设计辩护及伦理规范，帮助预判拒稿风险并优化稿件以通过严格审查。
Trigger Scenarios
投稿前压力测试稿件
解读决定信并设定预期
理解机制与量化设计的重要性
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill eursr-review-process -g -y
SKILL.md
Frontmatter
{
"name": "eursr-review-process",
"description": "Use when you need to understand how the European Sociological Review (ESR) evaluates a manuscript — double-blind peer review, what comparative quantitative reviewers weigh, decision categories, and the ethics rules (anonymity, no simultaneous submission). Sets expectations and shapes the paper to survive review; it does not contact editors."
}
Review Process (eursr-review-process)
Knowing how ESR reviews helps you pre-empt the failure modes before submitting. ESR uses double-blind review and draws reviewers from the comparative quantitative-sociology community, so a paper must read credibly to experts who scrutinize the comparative/longitudinal design and the modeling.
When to trigger
- Before submitting, to stress-test the manuscript against likely reviewer objections
- Interpreting a decision letter and setting expectations
- Understanding why a portable mechanism and a defensible quantitative design both matter
How ESR review works
- Double-blind review. Neither authors nor reviewers are identified; the manuscript must be
completely anonymous (no author names, identifying acknowledgments, or identifying self-citation
wording). Prepare accordingly (see
eursr-submission). - Editorial screening. Editors assess fit, comparative/theoretical contribution, and the length-vs-contribution balance; weak-fit, single-country-descriptive, or out-of-scope papers may be declined without full external review. Make the comparative mechanism obvious early.
- External review. Expert reviewers assess the contribution, the theory and hypotheses, the comparative/panel design, the modeling (level, clustering, invariance, few-cluster inference), and the evidence-to-claim link.
- Decisions. Reject, revise and resubmit (major or minor), or (rarely on first round) accept. R&R is the normal path; expect substantial revision. Replication packages are checked around conditional acceptance for statistical/computational work.
- Ethics. Submitting elsewhere while under ESR review is not allowed; prior appearances must be disclosed; English quality is the author's responsibility.
What reviewers weigh
| Reviewer asks | You answer with |
|---|---|
| Does this move a comparative debate? | explicit portable mechanism + comparative leverage |
| Is the design right for the claim? | the design defense in eursr-research-design |
| Is the modeling correct? | right level/clustering, invariance, few-cluster inference (eursr-data-analysis) |
| Are claims warranted by the evidence? | intervals, robustness, honest scope |
| Is the contribution distinct from prior work? | positioning in eursr-literature-positioning |
Shape the paper to pass
- Make the comparative mechanism and hypotheses explicit in the introduction.
- Anticipate the toughest modeling objection (measurement equivalence, macro-N inference) and answer it.
- Present robustness and leave-one-country-out checks honestly — reviewers trust candor.
- Engage the comparative frontier, not just one national literature.
- Have the replication package ready in spirit even before it is requested.
Stage-by-stage failure points
| Stage | What stops a paper here | Pre-empt by |
|---|---|---|
| Editorial screening | single-country / weak comparative fit | front-loading the comparative mechanism |
| Anonymity integrity | identifying wording or acknowledgments | the eursr-submission anonymity pass |
| Review — contribution | "adds a coefficient, not a mechanism" | a portable macro–micro claim |
| Review — design | comparison/panel can't identify the claim | the design defense + adjudication sentence |
| Review — modeling | wrong level / fragile macro inference | df-aware SEs, invariance, leave-one-out |
Worked micro-example (illustrative)
A multilevel attitudes paper is mock-reviewed before submission.
Screening risk: reads as 24-country description → reframe around the contextual mechanism (how welfare
generosity reshapes the individual link between insecurity and redistribution preference)
Contribution reviewer: "is there a mechanism, not just a country pattern?" → cross-level interaction headline
Modeling reviewer: "few clusters; invariance?" → wild cluster bootstrap + reported invariance level
Transparency reviewer: "package?" → DAS + Zenodo deposit ready (statistical → not exempt)
Predicted outcome: major R&R, not first-round accept (typical at ESR for a promising paper)
Stress-testing against the panel before submission converts likely screening and modeling failures into a clean R&R path.
Referee pushback → ESR-specific fix
- "Why ESR and not a national journal?" → Surface the comparative mechanism on the first page; ESR screens hardest on comparative/theoretical contribution.
- "Your macro inference is fragile." → Use df-aware methods and temper the country-level claim.
- "You expected an accept." → Plan for a substantial R&R; first-round acceptance is rare at ESR.
Calibration anchors
- Contribution and modeling correctness are both load-bearing. ESR rarely advances a paper strong on only one; the double-blind panel weights the portable mechanism and the comparative modeling together.
- Candor reads as competence. Expert reviewers find fragile macro inference and non-equivalent measures; reporting them first builds trust that carries a borderline paper.
- Confirm decision-category wording against the current guidelines if you need exact labels — the broad shape (reject / major-minor R&R / rare accept) is stable.
Anti-patterns
- A single-country descriptive paper sent to a comparative flagship
- Hiding fragile macro-N inference or non-equivalent measurement
- Expecting acceptance without a serious R&R round
- Treating a modeling reviewer's standards as illegitimate rather than addressing them
Output format
【Comparative contribution】portable mechanism + leverage clear? [Y/N]
【Design】defensible for the claim? [Y/N]
【Modeling】level/clustering/invariance/few-cluster handled? [Y/N]
【Evidence→claim】warranted and candid? [Y/N]
【Realistic outcome】reject / major-or-minor R&R / (rare) accept
【Next】eursr-submission (or eursr-rebuttal if decided)
Supplementary resources
../../resources/official-source-map.md— double-blind review, ethics, OUP/ECSR submission norms
Version History
- 1839142 Current 2026-07-05 13:13
