aaai-artifact-evaluati…
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without…
Use when stress-testing the LOGIC of an Academy of Management Review (AMR) theory manuscript — checking logical coherence, running thought experiments and counterfactuals, addressing alternative explanations and disconfirming cases, and verifying each proposition follows from
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill amr-data-analysis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/amr-data-analysisContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when stress-testing the LOGIC of an Academy of Management Review (AMR) theory manuscript — checking logical coherence, running thought experiments and counterfactuals, addressing alternative explanations and disconfirming cases, and verifying each proposition follows from
name: amr-data-analysis description: Use when stress-testing the LOGIC of an Academy of Management Review (AMR) theory manuscript — checking logical coherence, running thought experiments and counterfactuals, addressing alternative explanations and disconfirming cases, and verifying each proposition follows from its argument. This is ARGUMENT DEVELOPMENT, NOT data analysis; AMR publishes no datasets, no statistics, and no empirical results.
> **AMR publishes NO empirical data.** There is nothing to estimate, plot, or test. The > "analysis" in an AMR paper is the *analysis of the argument itself*: does each > proposition follow logically from the constructs and mechanisms? At AMR, logical > soundness plays the role that statistical rigor plays at empirical journals.
This skill replaces an empirical "identification + robustness" stage. The mapping:
| Empirical sibling (AMJ/ASQ/SMJ) | AMR theory analog | |---------------------------------|-------------------| | Identification strategy (IV, DiD, RD, matching) | Generative **mechanism** — the *why* (Whetten 1989, DOI 10.5465/amr.1989.4308371) | | Robustness checks / alternative specifications | **Internal consistency** + counterfactual probes on premises | | Ruling out confounders | Engaging and bettering the strongest **rival theory** | | Replication package (data + code) | **Transparent reasoning** — premises and derivations a reader can re-derive | | "Estimates are significant and robust" | **Propositions are falsifiable in principle** (AMR's "testable knowledge-based claims") |
There is no instrument, no parallel-trends test, no placebo here; their presence signals a misfiled empirical paper.
Run every proposition through these before drafting.
For each Pn, write the chain explicitly: premise → premise → mechanism → conclusion. If any step is missing, the proposition is asserted, not derived. Use a Toulmin frame: claim / grounds / warrant / backing / rebuttal. The *warrant* (the mechanism that licenses the inference) is where most theory papers are thin.
Manipulate the focal construct in your head and trace the consequence: "If construct X rose sharply while everything else held, what does the theory predict for Y, and is that prediction sensible?" Then run the counterfactual: "Under what condition would X move and Y *not* follow?" If the counterfactual is plausible and unexplained, you are missing a boundary condition (route back to `amr-theory-development`).
For each proposition, name the strongest *rival* theoretical account of the same relationship. Then either (a) show why your mechanism is more complete/parsimonious, or (b) integrate the rival as a boundary condition. Ignoring rivals is the fastest path to a reject — reviewers *are* the rival theorists.
Actively look for a case where the proposition should fail. A theory that "explains everything" explains nothing. Either the disconfirming case is covered by a stated boundary condition, or the proposition needs to be narrowed.
Exemplar: Oliver (AMR 1991, DOI 10.5465/amr.1991.4279002) "analyzes" by argument — deriving a typology and propositions from antecedent conditions and addressing why organizations might resist rather than conform (the rival expectation) — all logic, no data.
【Per-proposition logic】P1: chain ok? / gap at warrant? ... Pn 【Thought experiments run】[focal construct → predicted consequence] 【Counterfactuals → boundary conditions】[...] 【Alternative explanations handled】[rival → resolution] 【Disconfirming cases】[case → covered by boundary / narrow proposition] 【Coherence】consistent / non-circular / sufficient / parsimonious : pass/fix 【Next s
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