Hubert Ronald

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Modeling ​

Table of contents ​

Product objective ​

Models support identification and explanation of retention risk while preserving human review.

Prediction boundary ​

Every model must define:

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population
prediction target
time horizon
feature cutoff
exclusion criteria
decision context

Evaluation ​

Evaluation should include:

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discrimination
calibration
precision and recall
threshold behavior
temporal validation
subgroup analysis
business interpretation

No single metric should define readiness.

Explainability ​

Outputs should include structured evidence:

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risk score
important signals
confidence or uncertainty
data limitations
recommended next review

Resume Intelligence ​

Resume Intelligence may provide structured context extraction and transparent signals. It must not infer unsupported personality or psychometric traits.

Retention Advisor ​

The advisor combines validated signals, evidence, policy, and optional provider output into reviewable recommendations.

The advisor is decision support, not an autonomous employment decision-maker.

Limitations ​

Psychometric Intelligence is outside v1.0 until supported by appropriate data, validated instruments, fairness analysis, privacy review, and responsible interpretation.