Qualifying paper and dissertation support site

Tertiary Algorithmicity

A working resource for turning the qualifying paper into a dissertation architecture: core claims, chapter movement, reading clusters, committee questions, and writing routines for a project on AI, composition, media ecology, and productive friction.

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Use this first

Four entry points.

The original interactive overview had strong conceptual energy. This version keeps that center, but makes the site more useful as a live companion for drafting, committee preparation, and resource organization.

01 / Bridge

Paper to dissertation

Clarify what the qualifying paper proves and what the dissertation must still build.

Map the expansion
02 / Architecture

Chapter movement

Track the project as a sequence of claims, cases, methods, and pedagogical implications.

View chapters
03 / Library

Resource clusters

Filter theoretical, methodological, pedagogical, and writing resources by project stage.

Open library
04 / Practice

Writing routines

Use repeatable protocols for synthesis, chapter planning, revision, and committee response.

Start workflow
Conceptual bridge

What changes after the qualifying paper?

The qualifying paper can establish the conceptual problem. The dissertation needs to show what the problem does across histories, interfaces, classrooms, assessment systems, and writing practices.

Qualifying paper

  • Defines tertiary algorithmicity as a shift in writing's technical conditions.
  • Shows why fluency, speed, and output cannot be treated as simple gains.
  • Frames friction as a condition for judgment rather than a defect to remove.
  • Builds the theoretical vocabulary for AI-mediated composition.

Dissertation

  • Extends the argument through cases, pedagogical designs, and institutional stakes.
  • Distinguishes useful automation from unproductive success.
  • Turns friction into a design principle for assignments and assessment.
  • Contributes a framework teachers can use without reducing writing to compliance.

Working claim

AI writing systems do not merely add new tools to old composing processes. They reorganize the temporal, cognitive, and social conditions under which writing becomes meaningful, assessable, and teachable.

Dissertation architecture

Chapter map.

Use the tabs to test whether each chapter has a distinct job. The sequence below is provisional by design: it keeps the dissertation from becoming one large theory chapter wearing several hats.

Resource library

Find the right material for the current task.

This is a lightweight research dashboard. Search by keyword, filter by project stage, or jump through clusters when you need a specific kind of support.

No resources match that combination yet. Clear a filter or add another resource card to the data list.
Writing workflow

Repeatable routines.

These routines keep the project moving without pretending that all writing tasks are the same. Use them as checkpoints before advisor meetings, committee drafts, and chapter revisions.

Weekly synthesis

  1. Name one claim that became clearer this week.
  2. Identify one source that changed the claim rather than merely supporting it.
  3. Write a five-sentence bridge from reading to chapter draft.
  4. Archive one paragraph that is interesting but not currently load-bearing.

Chapter stress test

  1. State the chapter's job in one sentence.
  2. List the evidence it uniquely contributes.
  3. Mark any section doing work that belongs elsewhere.
  4. Draft the transition that explains why the next chapter must follow.

Committee prep

  1. Write the strongest objection to the central claim.
  2. Prepare a version of the answer for theorists, teachers, and administrators.
  3. Separate negotiable structure from non-negotiable contribution.
  4. Bring two concrete decisions that the committee can help resolve.
Prompt and question lab

Generate a useful next move.

Select a mode and the site will produce a reusable prompt or committee question. The goal is not to outsource the thinking, but to stage the next encounter with the material.

Choose a mode

Each mode is tuned to a different research action: synthesis, revision, advising, teaching, or methodological design.


          

        

      

    


    

      

        

          

            
Open decisions

            
Questions worth keeping visible.

          

          
The project will improve if these decisions stay explicit. They are not problems to hide; they are the dissertation's design surface.

        

        

          

            Scope
            
How much AI history belongs here?

            
The dissertation needs enough genealogy to make the present legible without becoming a broad history of computation.

          

          

            Evidence
            
What counts as a case?

            
Interface analysis, assignment design, student-facing policies, and institutional assessment can each serve as cases if the method is named clearly.

          

          

            Contribution
            
Who needs the framework?

            
The argument should speak to composition theorists, writing teachers, WPA administrators, and researchers studying human-AI mediation.