amr-data-analysis

GitHub

用于AMR理论稿件的逻辑与论证审查,非数据分析。检查命题推导、运行反事实思维实验、处理替代解释及证伪案例,确保理论内在一致性与逻辑严密性。

Academy-of-Management-Review-Skills/skills/amr-data-analysis/SKILL.md brycewang-stanford/Awesome-Journal-Skills

触发场景

验证命题是否由前提逻辑推导得出 对理论进行对抗性测试或反事实推演 回应审稿人可能提出的替代解释 发现论证链条中存在隐含跳跃

安装

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill amr-data-analysis -g -y
更多选项

非标准路径

npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Academy-of-Management-Review-Skills/skills/amr-data-analysis -g -y

不安装直接使用

npx skills use brycewang-stanford/Awesome-Journal-Skills@amr-data-analysis

指定 Agent (Claude Code)

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill amr-data-analysis -a claude-code -g -y

安装 repo 全部 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --all -g -y

预览 repo 内 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --list

SKILL.md

Frontmatter
{
    "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."
}

Argument Development & Logic Check (amr-data-analysis)

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.

The empirical-analog reframe (keep the folder, change the content)

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.

When to trigger

  • Propositions are written but you are not sure they actually follow from the argument
  • The theory "feels right" but has not been adversarially tested
  • A reviewer would raise an alternative explanation you have not addressed
  • The argument chain has hidden leaps between premises

The four logic tests

Run every proposition through these before drafting.

1. Premise-to-conclusion check (per proposition)

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.

2. Thought experiment / counterfactual

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).

3. Alternative-explanation audit

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.

4. Disconfirming-case search

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.

Internal-coherence checks across the whole theory

  • Consistency: no two propositions contradict each other (unless the tension is the point and is theorized). Constructs mean the same thing throughout — no concept drift (a core Suddaby construct-clarity criterion, AMR 2010, DOI 10.5465/amr.2010.0419).
  • Non-circularity: a construct is not defined by its effects, then used to explain those effects.
  • Sufficiency: the constructs and mechanisms are enough to generate the propositions — nothing is smuggled in mid-argument.
  • Parsimony: every construct earns its place; drop any that does no logical work.

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.

Checklist

  • Each proposition has an explicit premise → mechanism → conclusion chain
  • The warrant (mechanism) for each inference is stated, not assumed
  • A thought experiment has been run on each focal relationship
  • Counterfactuals are addressed by boundary conditions, not ignored
  • The strongest alternative explanation for each proposition is named and handled
  • A disconfirming case has been sought for each proposition
  • The theory is internally consistent, non-circular, sufficient, and parsimonious
  • No empirical evidence is invoked as proof (AMR has none)

Anti-patterns

  • Propositions presented as self-evident, with the argument left to the reader
  • Hand-waving the mechanism ("it stands to reason that...")
  • Defending the theory by asserting it would be "supported by data" — there are no data
  • Ignoring the obvious rival theory the reviewers hold
  • A theory that cannot be wrong: no boundary, no disconfirming case, no rebuttal addressed
  • Circular reasoning: defining a construct by the outcome it is meant to explain

Output format

【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 step】amr-contribution-framing

版本历史

  • 1839142 当前 2026-07-05 12:14

同 Skill 集合

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AAAI-Skills/skills/aaai-workflow/SKILL.md
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AAMAS-Skills/skills/aamas-author-response/SKILL.md
AAMAS-Skills/skills/aamas-camera-ready/SKILL.md
AAMAS-Skills/skills/aamas-experiments/SKILL.md
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AAMAS-Skills/skills/aamas-reproducibility/SKILL.md
AAMAS-Skills/skills/aamas-review-process/SKILL.md
AAMAS-Skills/skills/aamas-submission/SKILL.md
AAMAS-Skills/skills/aamas-supplementary/SKILL.md
AAMAS-Skills/skills/aamas-topic-selection/SKILL.md
AAMAS-Skills/skills/aamas-workflow/SKILL.md
AAMAS-Skills/skills/aamas-writing-style/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-editor-strategy/SKILL.md
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Academy-of-Management-Annals-Skills/skills/amann-literature-synthesis/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-organizing-framework/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-proposal-framing/SKILL.md
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Academy-of-Management-Annals-Skills/skills/amann-revision/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-submission/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-tables-figures/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-topic-selection/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-workflow/SKILL.md
Academy-of-Management-Annals-Skills/skills/amann-writing-style/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-contribution-framing/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-data-analysis/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-literature-positioning/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-methods/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-rebuttal/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-review-process/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-submission/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-tables-figures/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-theory-development/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-topic-selection/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-workflow/SKILL.md
Academy-of-Management-Journal-Skills/skills/amj-writing-style/SKILL.md
Academy-of-Management-Review-Skills/skills/amr-contribution-framing/SKILL.md

元信息

文件数
0
版本
c82fe76
Hash
5f9d6a4d
收录时间
2026-07-05 12:14

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