Dynamic Criminogenic Need Domain Scoring Guide
Caller-defined needs evidence summary, not clinical diagnosis or compulsory program recommendation. This restricted caller-defined rubric has three independently declared criterion domains: independently established program need domain one, independently established need domain two, independently established need domain three. Scores 0–100, nonnegative calibrated weights; known-only normalized mean and unresolved weight retained. No universal validated model, population risk prediction, personal diagnosis or authorization.
Description
Dynamic criminogenic-need scores depend on a particular rubric and evidence date.
Dynamic criminogenic-need scores depend on a particular rubric and evidence date.1
A generic weighted summary does not establish a validated instrument or individual treatment need. Use this tool to summarize known criterion scores under caller weights and retain missing-evidence coverage.
When to use Dynamic Criminogenic Need Domain Scoring Guide
Use this tool to summarize known criterion scores under caller weights and retain missing-evidence coverage. Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.
How to use Dynamic Criminogenic Need Domain Scoring Guide and understand its results
- Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.
- Enter independentlyAnnotatedCriterionScores, callerCalibratedCriterionWeights, criterionKnownFlags, using the field meanings and rules below, then run the tool.
- Read result.knownWeightedScore, result.unknownWeightFraction, result.unknownCriterionIndices. Interpret each field using the units, signs and evidence rules below.
- If input validation fails, correct the reported field and run again. Before applying a successful result, check the stated reference scope, units, assumptions and any retained unknown evidence.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| independentlyAnnotatedCriterionScores | Independently annotated criterion scores | list of number | Required |
| callerCalibratedCriterionWeights | Caller calibrated criterion weights | list of number | Required |
| criterionKnownFlags | Criterion known flags; 1 means known and 0 means unknown; keep the same item order | list of number | Required |
Enter exactly three aligned finite criterion scores, nonnegative weights and binary known flags. Scores must lie in 0–100 even when marked unknown. Require positive total weight and positive known weight; known items with only zero weights do not suffice. Divide the known weighted sum by known weight, report unknown weight divided by total weight, and retain zero-based unknown indices. The generic rubric neither supplies an official instrument nor calibrates a probability.
knownScore=Σ(score_i×weight_i×known_i)/Σ(weight_i×known_i); unknownWeightFraction=Σ(weight_i×(1−known_i))/Σweight_i Apply the field units and exact ordering, boundary and evidence rules above.
| Output field | Meaning | Value type |
|---|---|---|
| result | Structured result containing the calculation or selected reference fields below | object |
| result.knownWeightedScore | Weighted mean over known criteria with positive known weight, on the supplied 0–100 scale | number |
| result.unknownWeightFraction | Unknown criterion weight divided by total criterion weight | number |
| result.unknownCriterionIndices | Zero-based positions of unknown criteria | list of values |
{
"input": {
"independentlyAnnotatedCriterionScores": [
20,
40,
60
],
"callerCalibratedCriterionWeights": [
1,
2,
1
],
"criterionKnownFlags": [
1,
1,
1
]
},
"output": {
"result": {
"knownWeightedScore": 40,
"unknownWeightFraction": 0,
"unknownCriterionIndices": []
}
}
}Limitations and assumptions
A generic weighted summary does not establish a validated instrument or individual treatment need. Results depend on the independently established measurement basis and the exact model assumptions above.
Every listed input requires an explicit value. Unexpected fields, incorrect value types, nonfinite numbers and sparse numeric arrays fail validation; tool-specific bounds and alignment rules apply as described above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful calculation that reports a false comparison or retains unknown evidence.
Alternative or Complementary methods
Use Risk Needs Responsivity Tier Classifier to examine a related aspect: Risk-needs-responsivity review involves an assessment instrument, needs evidence and accommodation context.
Use Classification Custody Score Points Model Calculator where its separate inputs and scope apply: Custody classification scores depend on a specific assessment instrument and context.
References
Similar or alternative tools
- Risk Needs Responsivity Tier Classifier
Risk-needs-responsivity review involves an assessment instrument, needs evidence and accommodation context.
- Classification Custody Score Points Model Calculator
Custody classification scores depend on a specific assessment instrument and context.