Interview scorecard template

Temporal Paradox Resolution Specialist interview scorecard

Evaluate Temporal Paradox Resolution Specialist candidates across 4 weighted areas: theoretical command, from theory to hardware or code, research judgement, and explaining it to non-specialists. Theoretical command leads at 35%, so probe command of closed timelike curves, Novikov self-consistency, and branching versus block-universe models; ask which formalism they use to classify. Use the rubric to compare role-specific evidence consistently.

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frontier research deep techcausal consistencyclosed timelike curvesparadox triagetimeline integrity
TL;DR
For theoretical command, look for evidence the candidate distinguishes self-consistency constraints from many-worlds branching fluently, and names the conditions under which each model predicts a resolvable paradox. For from theory to hardware or code, look for evidence the candidate points to working artefacts (a causal consistency checker, a divergence-tracking pipeline) with inputs, outputs, and observed failure modes. Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework

What to assess and how to score it

Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.

01
Evaluation factor

Theoretical command

35% weight

Probe command of closed timelike curves, Novikov self-consistency, and branching versus block-universe models; ask which formalism they use to classify a grandfather-type contradiction and why.

Evidence to listen for

  • Explains the underlying theory at the level the role demands, and can go a layer deeper when pushed
  • Knows which results are established and which are contested
  • Distinguishes their own contribution from the field's
  • Comfortable saying where the theory runs out

Five-point scoring guide

1
Poor

Recites terminology without understanding; cannot go one layer deeper.

2
Needs Improvement

Surface familiarity; conflates established results with speculation.

3
Satisfactory

Solid grasp of the core theory; thin at the frontier.

4
Very Good

Strong command; separates settled results from open questions.

5
Excellent

Distinguishes self-consistency constraints from many-worlds branching fluently, and names the conditions under which each model predicts a resolvable paradox.

02
Evaluation factor

From theory to hardware or code

30% weight

Ask what they actually built: chronology-protection simulations, causal graph solvers, timeline diff tooling, or intervention logs, and what ran in production versus stayed theoretical.

Evidence to listen for

  • Has built, simulated, or run something real, not only published about it
  • Knows the gap between the idealised model and the actual apparatus or system
  • Names the practical constraint that dominates in real conditions
  • Can describe a result that did not match prediction

Five-point scoring guide

1
Poor

Purely theoretical; no contact with implementation.

2
Needs Improvement

Some exposure but unaware of practical constraints.

3
Satisfactory

Has implemented work; understands the main real-world limits.

4
Very Good

Strong practical record; articulate about theory-versus-reality gaps.

5
Excellent

Points to working artefacts (a causal consistency checker, a divergence-tracking pipeline) with inputs, outputs, and observed failure modes.

03
Evaluation factor

Research judgement

20% weight

Test how they triage competing resolution strategies when evidence is thin: minimal-intervention rollback, quarantining a divergent branch, or accepting a stable loop. Look for stated cost of error.

Evidence to listen for

  • Chooses problems by tractability and value, not novelty alone
  • Knows when to abandon a line of work
  • Reads and evaluates others' results critically
  • Can say what would falsify their own approach

Five-point scoring guide

1
Poor

Chases novelty; no sense of tractability or when to stop.

2
Needs Improvement

Weak problem selection; persists past the point of value.

3
Satisfactory

Reasonable judgement within a defined programme.

4
Very Good

Selects problems well and knows when to abandon a line.

5
Excellent

Ranks candidate resolutions against explicit criteria (divergence magnitude, reversibility, observer impact) and states which options they deliberately ruled out.

04
Evaluation factor

Explaining it to non-specialists

15% weight

Judge how they brief non-specialists: can they explain a bootstrap paradox or entropy accounting to operations staff and regulators without collapsing into jargon or hand-waving?

Evidence to listen for

  • Explains the work to an engineer, an executive, or a funder without either mystifying or dumbing it down
  • Writes clearly
  • Collaborates across disciplines
  • Makes the case for resources in terms the audience cares about

Five-point scoring guide

1
Poor

Cannot communicate outside their specialism.

2
Needs Improvement

Explanation is either impenetrable or hollow.

3
Satisfactory

Adequate with technical peers; less effective with lay audiences.

4
Very Good

Explains clearly to specialists and non-specialists alike.

5
Excellent

Uses concrete analogies and diagrams, separates established constraints from speculation, and states confidence levels plainly to lay decision-makers.

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