jev-quadrant-v1 · CC BY 4.0

Open methodology

This page is the public summary of spec/jev-quadrant-v1.md. The spec and JSON Schemas are the source of truth.

Thesis

A Gartner-style quadrant is an analyst drawing. Jev Quadrant is a function: evidence pack in, calibrated probabilities out. TypeSafe Jev (System One, `jev-latest`) does not write an essay about vendors. It answers typed `noul` and `choice` questions. We average the axis answers, size an ellipse from evidence mass and disagreement, and show the full four-cell distribution.

Default axes

• Proven Execution (X) — delivery, adoption, reliability, cadence.
• Validated Direction (Y) — specific strategy, backed by artifacts, distinct, invested.

Cells

We do not use Leaders, Challengers, Visionaries, or Niche. Membership is a Jev `choice`, not a hard 0.5 cut on the plotted point.

• Anchored — both axes strong
• Directed — direction ahead of delivery
• Operational — delivery ahead of direction
• Forming — both thin or contradicted

Rubric questions

1. exec_shipped · x

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Has this entity shipped a generally available product used by third parties?

   true: Independent public evidence shows a generally available product used by third parties.

2. exec_adoption · x

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Is there credible adoption evidence?

   true: Credible adoption evidence exists: named customers, published user or download counts, case studies, or equivalent.

3. exec_reliability · x

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Is there evidence of reliability, quality, security/compliance, or operational maturity?

   true: Evidence of reliability, quality, security/compliance, or operational maturity (uptime, incidents handled, certifications, long-running open-source project).

4. exec_cadence · x

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Is there evidence of continued delivery after launch?

   true: Evidence of continued delivery after launch (dated releases, changelog, subsequent features).

5. dir_strategy · y

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Is there a specific, consistent, dated public strategy or roadmap?

   true: A public strategy or roadmap is specific, consistent, and dated.

6. dir_backed · y

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Are strategy or roadmap claims backed by shipped artifacts in the evidence pack?

   true: Roadmap or strategy claims are backed by shipped artifacts in the evidence pack.

7. dir_distinct · y

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Is the evidenced direction distinct from generic category copy?

   true: The evidenced direction is distinct from generic category copy.

8. dir_invested · y

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Is there evidence of sustained investment in this product?

   true: Evidence of sustained investment (funding used for the product, research, open-source velocity, or platform expansion).

9. quadrant · membership

   Use only the supplied state. Do not use prior knowledge that is not represented as evidence items. If evidence is thin, return a probability near 0.5 with the understanding that uncertainty is handled separately. Assign the entity to one Jev Quadrant cell. Do not use a hard 0.5 cut. Weigh the full evidence pack.

   ANCHORED · DIRECTED · OPERATIONAL · FORMING

Scoring math

Axis score is the mean of that axis’s `noul` values. Recency weight is 2^(-d/H) with half-life H = 180 days. Evidence mass M is the sum of weights. Uncertainty is

u = clamp(0.08 + 0.45/(1+M) + 0.35·σ, 0.05, 0.42)
ellipse semi-axis = clamp(0.55·u, 0.04, 0.28)

Cache key is SHA-256 of the canonical request JSON. Repeat views do not re-call Jev.

Worked example (labelled)

Limitations

• Public evidence under-represents silent production use.
• Thin packs produce large ellipses, not confident ranks.
• Absence from a topic is not a negative score.
• This is not investment, procurement, or legal advice.
• If `TYPESAFE_API_KEY` is missing, the UI shows not-yet-scored. We never fabricate live probabilities.

License: specification CC BY 4.0; application code MIT. Attribution: Jev Quadrant Framework v1.0.0.