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Asq Theory Development

Community
franklee16
asq-theory-development

Use when building the theoretical engine for an Administrative Science Quarterly (ASQ) manuscript — mechanisms, process vs. variance logic, constructs, and boundary conditions. Builds the argument; it does not select methods or run analysis.

Overview

Publisherfranklee16
Repositoryacademic-research-skills
Skill nameasq-theory-development
Stars
225
Forks
34
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by franklee16 on GitHub. Read the source before you install it.

Installation

Install the Asq Theory Development AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Administrative-Science-Quarterly-Skills/skills/asq-theory-development
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/franklee16/academic-research-skills.git /tmp/academic-research-skills
mkdir -p .claude/skills
cp -r /tmp/academic-research-skills/Awesome-Journal-Skills-main/Administrative-Science-Quarterly-Skills/skills/asq-theory-development .claude/skills/asq-theory-development
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Asq Theory Development in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Asq Theory Development on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Asq Theory Development is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Theory Development (asq-theory-development)

When to trigger

  • You have a puzzle (from asq-topic-selection) but no theoretical machinery to explain it
  • Your "theory" is a box-and-arrow diagram with labeled constructs but no mechanism
  • You are unsure whether your phenomenon needs a process theory or a variance theory
  • Reviewers say the theory is "thin," "post hoc," or "a relabeling of the finding"

Process theory vs. variance theory

This is the central choice at ASQ. Get it right before drafting.

  • Variance theory explains how much of an outcome varies with antecedents: X → Y, with moderators/mediators. Appropriate for "whether and under what conditions" questions, typically quantitative.
  • Process theory explains how and why something unfolds over time: sequences, events, feedback, transformation. Appropriate for emergence, becoming, contestation, and dynamics — typically qualitative/inductive.

ASQ punishes variance framing forced onto a process question: if your data show a sequence of events transforming an organization but you write it as "factor A increases outcome B," reviewers will say the theory and phenomenon are mismatched. Match the form of the theory to the form of the phenomenon. ASQ's lineage makes process and interpretive theorizing fully legitimate as the main contribution — this is a real difference from journals where the variance/hypothesis template is the implicit standard. Barley's (1986) ASQ study of CT scanners, for instance, theorized structuring as a process rather than estimating an effect of technology on structure.

Mechanism first

A construct is not a mechanism. State the generative mechanism — the social/organizational process that produces the relationship or sequence:

  • Name the actors and what they are doing (sensemaking, competing, imitating, categorizing, coordinating, resisting). ASQ's sociology-of-organizations roots mean collective and field-level mechanisms (mimetic, normative, and coercive isomorphism in the DiMaggio & Powell 1983 sense) are as welcome as micro ones.
  • Name the social structure in which they act (field, hierarchy, network, category system, status order)
  • Specify the causal/processual logic: why does this actor, in this structure, produce this outcome or this next step?
  • Specify boundary conditions: where does the mechanism hold, weaken, or reverse?

A good test: could a reader predict a new, non-obvious implication from your mechanism? If not, you have a label, not a theory.

For inductive papers

If theory is emergent (grounded), this skill still applies — but in reverse order:

  • Theory is the output, presented after the data structure (see asq-data-analysis)
  • Still required: a named mechanism, a process model (often a figure with phases/feedback), and a clear statement of what is novel relative to existing organizational theory
  • A grounded, inductively-built theory can be the entire contribution at ASQ — it need not be a stepping stone to a later deductive test, as it might be framed elsewhere
  • Avoid "theory by adjective": calling a pattern "dynamic" or "recursive" without specifying the process

For deductive papers

  • Hypotheses must be derived, each with an explicit causal logic paragraph — not asserted
  • Each hypothesis should connect back to the same core mechanism (avoid a "bag of hypotheses")
  • Moderators must be theoretically motivated (why this boundary?), not data-driven fishing

Checklist

  • Process vs. variance form matches the phenomenon
  • A named generative mechanism (actors + structure + logic), not just constructs
  • Boundary conditions stated (where it holds / weakens / reverses)
  • Mechanism yields at least one non-obvious, testable/observable implication
  • Constructs are defined precisely and consistently with the literature
  • For deductive: each hypothesis has its own derivation paragraph tied to the mechanism
  • For inductive: a process/theory model figure is planned, with novelty stated

Anti-patterns

  • Box-and-arrow models with no mechanism ("constructs in search of a story")
  • Variance framing for a process phenomenon (or vice versa)
  • Hypotheses asserted rather than derived; a moderator zoo with no logic
  • "Theory by adjective" — naming a pattern instead of explaining it
  • Borrowing a fashionable construct as a veneer over an under-theorized finding

Output format

【Theory form】process / variance + why it matches the phenomenon
【Core mechanism】actors + structure + causal/processual logic
【Boundary conditions】where it holds / weakens / reverses
【Novel implication】the non-obvious prediction or insight
【Deductive only】hypotheses + derivation status
【Next step】asq-literature-positioning

Frequently asked questions

What does the Asq Theory Development AI skill do?

Use when building the theoretical engine for an Administrative Science Quarterly (ASQ) manuscript — mechanisms, process vs. variance logic, constructs, and boundary conditions. Builds the argument; it does not select methods or run analysis.

Why use Asq Theory Development on TypingMind?

Because you install it once and use it with any model. Asq Theory Development is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Asq Theory Development in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/franklee16/academic-research-skills/tree/master/Awesome-Journal-Skills-main/Administrative-Science-Quarterly-Skills/skills/asq-theory-development. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Asq Theory Development?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Asq Theory Development?

As many as you like. As long as a model supports skills, you can use Asq Theory Development with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Asq Theory Development AI skill free?

It is published on GitHub by franklee16. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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