# Evidence model

## Research basis

Treat the popular `0→1`, `1→10`, and `10→100` language as a practical stage
metaphor, not a validated personality taxonomy.

- Peter Thiel popularized `0→1` for creating something new versus copying an
  existing model. The later three-stage extension is practitioner language.
- March's exploration/exploitation model supports a real distinction between
  searching for new possibilities and refining existing capabilities.
- D'Acunto, Tate, and Yang found that startups with more diverse collective
  industry skillsets grew faster; a one-standard-deviation increase in skill
  diversity was associated with 16% higher five-year employment growth and
  10% higher sales growth from the mean.
- A systematic review of entrepreneurial-team diversity describes diversity as
  a double-edged sword: knowledge breadth can help while disparity, separation,
  and conflict can hurt.
- De Cooman et al. found the best team outcomes when members perceived both
  supplementary fit (important similarities) and complementary fit (different
  useful capabilities), mediated by cohesion.
- Lewis's transactive-memory research supports making expertise legible:
  effective teams know who knows what and can coordinate that expertise.

Sources:

- March, *Exploration and Exploitation in Organizational Learning*:
  https://doi.org/10.1287/orsc.2.1.71
- D'Acunto, Tate, and Yang, *Entrepreneurial Teams: Diversity of Skills and
  Early-Stage Growth*: https://doi.org/10.2139/ssrn.3750982
- Klotz et al., *Entrepreneurial team diversity — A systematic review and
  research agenda*: https://doi.org/10.1016/j.emj.2022.10.004
- De Cooman et al., *Creating Inclusive Teams Through Perceptions of
  Supplementary and Complementary Person–Team Fit*:
  https://doi.org/10.1177/1059601115586910
- Lewis, *Measuring Transactive Memory Systems in the Field*:
  https://doi.org/10.1037/0021-9010.88.4.587

## Operational model

Assess two independent axes.

### Startup-stage contribution

| Vector | Observable evidence |
| --- | --- |
| `zero_to_one` | frames unmet needs; runs discovery; invents; prototypes under ambiguity; creates a first working artifact |
| `one_to_ten` | interviews users; iterates from evidence; wins early customers; establishes a repeatable product/GTM loop |
| `ten_to_hundred` | designs reliable systems; delegates; hires; manages quality and economics; scales repeatable operations |

### Functional contribution

| Vector | Observable evidence |
| --- | --- |
| `problem_discovery` | finds important unmet needs and tests assumptions |
| `product` | chooses scope, sequences value, and integrates feedback |
| `engineering` | builds and operates technical systems |
| `design` | creates understandable, usable experiences |
| `go_to_market` | positions, sells, distributes, and learns from the market |
| `operations` | creates repeatable delivery and reliable processes |
| `people_leadership` | recruits, aligns, coaches, and resolves conflict |
| `capital_partnerships` | secures resources and durable external alliances |

Do not equate a job title with evidence. One outcome may support several
vectors, but state the linkage explicitly.

## Evidence hierarchy

Weight evidence in this order:

1. verified customer or operational outcome;
2. shipped public artifact with clear ownership;
3. repeated responsibility with a concrete result;
4. specific peer or collaborator feedback;
5. self-reported preference.

Preference indicates energy and desired role, not demonstrated capability.
Require at least two independent strong evidence items for a high-confidence
`strong` label. Use `unknown` when evidence is absent.

## Matching rule

Maximize:

1. coverage of explicit stage and functional gaps;
2. overlap in project purpose, collaboration mode, and operating principles;
3. credible, current evidence;
4. reciprocal usefulness.

Check separately for commitment, decision rights, risk tolerance, pace,
communication norms, and conflict handling. These are not "soft extras";
complementary skills without operating compatibility can make a worse team.

Never infer compatibility from demographics or sensitive traits.