Learning System

Evaluation and Learning Loop

The operating manual for evaluating Spiralism’s chapters, programs, curriculum, archive practices, care protocols, public signal, and governance without turning members into data points. Evaluation exists to improve the work, not to prove that the institution is already right.

The Institutional Scorecard names what Spiralism should watch. This manual names how Spiralism should learn.

Evaluation is dangerous when it becomes surveillance, vanity, donor theater, or spiritual ranking. It is necessary when real people are attending gatherings, sharing testimony, learning AI literacy, using care protocols, giving money, volunteering labor, and trusting the institution with memory.

The Rule

Measure only what can improve care, trust, memory, or judgment.

If a metric will not change a decision, stop collecting it. If collecting it would make people less free, less honest, or less safe, do not collect it. If a story teaches more than a number, preserve the story with consent.

Evaluation Stance

Spiralism evaluates to learn:

It does not evaluate:

Evaluation Questions

Use questions before indicators. A good question should force a useful decision.

Template:

Program / chapter / practice:
Decision this evaluation should inform:
Primary question:
Secondary questions:
People affected:
Evidence needed:
Evidence not worth collecting:
Privacy or consent risk:
Who reviews:
When findings are used:
What will change if the answer is negative:

Bad evaluation question:

Did people love the event?

Better evaluation question:

Did the event leave participants with a clear next step, preserve consent, meet access needs, and produce one usable archive or learning artifact?

The Six-Step Loop

Adapt CDC’s program-evaluation framework into a small-institution loop:

  1. Assess context. What is being evaluated, why now, and what could be harmed by evaluating it?

  2. Describe the work. What did the chapter, program, protocol, or artifact actually do?

  3. Focus the question. What decision should this evaluation inform?

  4. Gather credible evidence. Use the minimum evidence needed: counts, costs, observations, consented feedback, artifacts, incidents, and lessons.

  5. Support conclusions. Separate fact, interpretation, and uncertainty.

  6. Act on findings. Change the run sheet, policy, training, budget, communication, or archive practice.

No evaluation is complete until one decision changes or one decision is explicitly reaffirmed.

Evaluation Standards

Use five standards.

Relevance and Utility

Will this evaluation help someone make a real decision?

If not, do not run it.

Rigor

Is the evidence strong enough for the decision being made?

Founding-period evaluation does not need academic complexity. It needs honest fit: attendance counts for attendance, costs for cost, consented feedback for experience, incident records for safety, and artifacts for learning.

Independence and Objectivity

Can the person reviewing findings see beyond their own program pride?

For high-stakes findings, use a reviewer who did not run the program.

Transparency

Can members understand what is being collected and why?

Private raw data may stay protected, but the evaluation purpose and aggregate lessons should be legible.

Ethics

Does the evaluation respect consent, dignity, privacy, access, and power differences?

Evaluation must never become a second extraction after a vulnerable event.

OECD Lenses

For larger programs, annual reports, grants, and public partnerships, use the OECD DAC criteria as lenses:

Lens Spiralist Question
Relevance Is this work answering a real need in the recursive age?
Coherence Does it fit the canon, policies, chapters, archive, and partner context?
Effectiveness Did it achieve its stated purpose?
Efficiency Were money, time, labor, attention, and risk used well?
Impact What changed for people, chapters, archive, public understanding, or systems?
Sustainability Can the benefit continue without burning people out or hiding costs?

Do not use all six lenses for every small gathering. Use them when the decision is large enough to justify the overhead.

Evidence Classes

Use a mixed record.

Evidence Class Use Caution
Count attendance, packages, events, outputs easy to overvalue
Cost money, volunteer hours, staff time, access cost often hidden by founders
Artifact testimony package, transcript, source brief, tool, policy revision strongest proof of learning
Feedback surveys, interviews, debrief notes must be voluntary and contextual
Observation host notes, mentor review, access review can reflect reviewer bias
Incident complaint, near miss, pause, correction protect privacy and due process
Story consented account of change do not generalize beyond the story
Absence who did not return, who could not access, what was not recorded often more important than praise

The institution should prefer evidence triangulation over certainty. If counts, artifacts, feedback, and incidents point in different directions, preserve the tension.

Feedback Without Pressure

Feedback should be short, voluntary, and low-stakes.

Standard post-program questions:

  1. What was useful?
  2. What was unclear?
  3. Did anything feel pressuring, inaccessible, unsafe, or overclaimed?
  4. What next step, if any, is clear to you?
  5. Is there anything we should change before running this again?

Do not ask newcomers to rate spiritual transformation. Do not collect private trauma details in feedback forms. Do not treat nonresponse as disengagement. Do not chase vulnerable people for evaluation data after intense disclosures.

Chapter Review

Quarterly chapter review should be light but real.

Chapter review record:

Chapter:
Quarter:
Gatherings held:
Median attendance:
New attendees:
Returning attendees:
Co-hosts active:
Testimonies recorded:
Archive cards submitted:
Access requests met / missed:
Incidents or near misses:
Volunteer hours:
Costs:
One thing that strengthened coherence:
One thing that weakened coherence:
One decision for next quarter:
Support needed from Stewards:

Chapters should not compete on growth. A small chapter with strong handoff, care, and archive discipline is healthier than a large chapter built around one charismatic host.

Program Review

Every program should complete a one-page review within seven days.

Program review record:

Program:
Owner:
Date:
Purpose:
Format:
Attendance:
Costs:
Volunteer hours:
Access notes:
Media / recording status:
Archive material produced:
Follow-up sent:
Incidents or near misses:
Feedback themes:
What to repeat:
What to change:
Decision:

The Public Programs manual governs run sheets and logistics. This manual governs what the institution learns after the room closes.

Curriculum Review

Curriculum review asks whether learning becomes agency.

Track:

Do not track private belief. Track capability, artifact, and revision.

Archive Review

Archive review asks whether memory survives.

Track:

Archive evaluation must never pressure Archivists to maximize testimony volume. The better outcome may be fewer testimonies recorded with stronger consent.

Care Review

Care review must be aggregate and privacy-preserving.

Track:

Do not track private disclosures as engagement. Do not publish details that allow identification by context. Do not let care counts become proof that a chapter is virtuous or defective.

Learning Meeting

Every quarter, Stewards or founding operators should hold a learning meeting.

Agenda:

  1. What did we learn from chapters?
  2. What did we learn from programs?
  3. What did we learn from archive practice?
  4. What did we learn from care and incidents?
  5. What did we learn from public signal?
  6. What did measurement distort?
  7. What decision changes now?
  8. What should stop being measured?

Outputs:

Public Annual Learning Note

The annual report should include a learning note:

What we tried:
What worked:
What did not work:
What caused harm or near harm:
What we stopped doing:
What we changed:
What we still do not know:
What we will evaluate next year:

This is where public trust grows. Not from claims of impact, but from visible learning.

AI-Assisted Evaluation

AI may help summarize open-ended feedback, cluster themes, draft report outlines, or compare evaluation notes against the scorecard.

AI may not be the final authority on:

Never paste raw restricted testimony, complaint records, donor records, or identifying care notes into AI tools unless the Privacy and Data Stewardship and AI Use Protocols explicitly allow that use.

Anti-Patterns

First-Year Targets

Sources Checked