本文へ移動
cccskills
無料GitHub で公開

aos-tables-figures

Use when building the exhibits of an Accounting, Organizations and Society (AOS) manuscript — data-inventory and evidence tables for qualitative work, cell-means and process-test tables for experiments, and figures that carry theoretical weight — in Elsevier-compatible format. Builds exhibits; it does not run the analysis (aos-data-analysis).

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.6 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Tables & Figures (aos-tables-figures)

When to trigger

  • A field paper has long quotations but no exhibit showing the evidentiary base
  • Experimental results lack a clean cell-means or contrast table
  • A figure decorates rather than argues (or a needed process figure is missing)
  • Formatting must be reconciled with Elsevier submission requirements

Exhibits by tradition — what AOS reviewers look for

Qualitative field / historical papers

  • Data-inventory table: interviews (number, roles, duration, period), observations (events, hours), documents (types, spans) — the single exhibit that preempts "how much data is behind this?"
  • Evidence table(s): conceptual claim or second-order theme in one column, representative field excerpts in the other, so the interpretive chain is inspectable without bloating the text.
  • Coding-structure exhibit where the paper's method warrants it: first-order codes → second-order categories → aggregate concepts, showing movement from informant language to theory.
  • Timeline or process figure for change studies: phases, key events, and where the accounting practice intervened.
  • Anonymize consistently — pseudonyms and role labels in exhibits must match the text and betray no site identity.

Experimental / survey papers

  • Cell-means table: means, SDs, n per condition; the predicted pattern visible at a glance.
  • Contrast/ANOVA table plus process results (mediation with bootstrap CIs) as exhibits, not prose asides.
  • An interaction figure with error bars when a moderation is the theory's signature; axis units interpretable, no truncated scales that exaggerate effects.
  • Survey papers: construct table (items, sources, reliabilities) and a correlation matrix.

Archival-with-theory papers

  • Descriptives, the main estimation table with clustering and fixed-effects structure stated in the notes, and magnitudes interpreted in institutional terms.

Self-containment and format

  • Every exhibit readable alone: title stating what it shows, sample/period, definitions, and the meaning of any markers in the notes.
  • Number tables and figures consecutively; place callouts in the text; Elsevier prefers editable source files for tables and high-resolution figure files at final stages — confirm current artwork specs in the AOS Guide for Authors before submission.
  • Keep exhibits inside the double-anonymized envelope: no author names in captions, file names, or embedded metadata.
  • Ration exhibits: each one must carry evidence or structure the argument; move genuinely supplementary material to an appendix or online supplement.

The one-sentence test

For every exhibit, write the sentence it proves ("Table 2 shows the interpretation rests on 74 interviews across four roles over 26 months"; "Figure 3 shows the effect reverses under high accountability"). If no sentence exists, cut the exhibit; if the sentence is central and no exhibit backs it, build one.

Checklist

  • (Qualitative) data-inventory table present; evidence/coding exhibits trace claims to material
  • (Experimental) cell means, contrasts, process tests, and the key interaction figure present
  • Every exhibit passes the one-sentence test and is self-contained
  • Pseudonyms/labels consistent across text and exhibits; anonymity preserved
  • Numbering, callouts, and artwork specs match the current Guide for Authors
  • No exhibit metadata or file name identifies the authors or the site

Anti-patterns

  • Quote dumps in tables — excerpts without the conceptual column that gives them a job.
  • Decorative frameworks: boxes-and-arrows figures that restate the table of contents.
  • Cell-means tables missing n or SDs, or interaction plots without uncertainty.
  • Exhibit inflation: ten tables where three would carry the argument.
  • Anonymity leaks through logos, letterheads, or document scans reproduced in figures.

Output format

【Exhibit list】each with its one-sentence job ...
【Data inventory (qual)】interviews / observations / documents tabulated? ...
【Process exhibits (exp)】cell means, contrasts, mediation, interaction figure ...
【Self-containment】titles, notes, definitions complete? ...
【Anonymity & format】pseudonyms consistent; Elsevier artwork specs checked ...
【Next step】aos-writing-style

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Awesome-Journal-Skills1,2482026年9月27日 更新

brycewang-stanford のスキルをすべて見る

このスキルの問題を報告する