算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
eursr-rebuttal【设计与创意】Use when writing the response to a European Sociological Review (ESR) revise-and-resubmit. ESR R&Rs typically demand substantial revision and reviewers focus on comparative design, measurement equivalence, and modeling, so the response must convert each reviewer while keeping the editor confident. Structures the response letter; it does not fabricate…
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An ESR R&R is the normal road to publication for a promising paper — and it usually asks for substantial revision. Reviewers focus on the comparative design, measurement equivalence, and the modeling (level, clustering, few-cluster inference), so the response letter must satisfy a quantitative skeptic without breaking the paper, while the editor adjudicates.
eursr-transparency-and-data).For each reviewer comment:
> [Quoted reviewer comment]
Response: [What we did / why we respectfully disagree].
Change: [Section/page/table-figure number where the revision appears].
Open with a short summary of the main changes to the editor; group by reviewer; end each entry with the location of the change so the editor can verify quickly.
| Comment type | Default response |
|---|---|
| Editor's decisive point | do it; never argue these away |
| Modeling/measurement check you can run (invariance, df SEs, LOO) | run it; report honestly even if mixed |
| "Add more countries / waves" | add if feasible; if not, justify the set and bound the claim |
| Request that dilutes the mechanism or comparative leverage | rebut respectfully with a reason |
A comparative attitudes paper gets an R&R where R1 doubts measurement equivalence and R2 thinks the macro effect rests on too few clusters.
R1: "Are the attitude scales comparable across countries?"
Response: Added configural/metric/scalar invariance tests (Appendix Table A3); scalar fails for 3
countries → re-estimated with partial scalar invariance; substantive conclusion unchanged. Change: §4.2.
R2: "24 countries can't support that macro claim."
Response: Re-ran macro inference with a wild cluster bootstrap and a Bayesian two-level model
(Table 5); interaction CI widens but excludes zero; macro claim tempered. Change: §5.1, Appendix B.
The letter concedes where evidence warrants, runs the modeling checks on their own terms, and protects the contribution by showing the cross-level result survives the stricter inference.
【Editor's decisive points】addressed first? [list]
【Coverage】every reviewer comment answered? [Y/N]
【Concede vs rebut】each tagged with evidence + change location
【Modeling/measurement checks】invariance / few-cluster / LOO run and reported? [Y/N]
【Contribution protected】no dilution of mechanism / comparative leverage? [Y/N]
【Anonymity + DAS/package updated】[Y/N]
【Next】resubmit via ScholarOne
../../resources/external_tools.md — invariance, few-cluster, and Bayesian multilevel tooling../../resources/official-source-map.md — ESR review model and ethics