Index

Key terms and where they are first defined or most thoroughly discussed.

A¶

• ACS PUMS data: Chapters 1, 2, 3

• Activation functions: Chapter 4

• Agentic AI: Chapter 13

• Agency (decision-making authority): Chapter 13

• Algorithmic bias: Chapter 8

• Attention mechanism: Chapter 11

• Automation bias: Chapter 14

• Autonomy dial: Chapter 13

B¶

• Backpropagation: Chapter 4

• Benchmark gaming: Chapter 14

• BERT: Chapter 11

• Bias, algorithmic: Chapter 8

• Bias, statistical: Chapter 8

• Blocking (record linkage): Chapter 5

• Bounded agency: Chapters 13, 14

C¶

• Calibration (fairness metric): Chapter 8

• Census APIs: Chapters 1, 2

• CIPSEA: Chapter 14

• Classification: Chapter 1

• Clustering: Chapter 6

• Cohen’s kappa: Chapter 12

• Compression Distortion (T3): Chapter 15

• Compression Fidelity (CF): Chapter 15

• Confidence-based routing: Chapter 12

• Confidential models: Chapter 10

• Confusion matrix: Chapter 1

• Context window: Chapters 12, 15

• Cross-validation: Chapter 2

• Curse of dimensionality: Chapter 6

D¶

• Decision trees: Chapter 3

• Demographic parity: Chapter 8

• Design effects: Chapter 5

• Differential privacy: Chapter 9

• Differential undercount: Chapter 8

• Dimension reduction: Chapter 6

• Disclosure risk: Chapter 9

E¶

• Early stopping: Chapter 4

• Embeddings: Chapter 11

• Enforcement gap: Chapter 10

• Entity resolution: Chapter 5

• Epsilon (privacy parameter): Chapter 9

• Equalized odds: Chapter 8

• Evaluation rubric (10-dimension): Chapter 14

F¶

• Fairness impossibility theorem: Chapter 8

• Fairness metrics: Chapter 8

• False State Injection (T2): Chapter 15

• FCSM quality standards: Chapter 14

• FedRAMP: Chapter 12

• Feature importance: Chapters 2, 3

• Feature importance stability: Chapter 3

• Fine-tuning: Chapter 11

• FSRDC: Chapter 9

G¶

• Geographic codes (FIPS, GEOIDs): Chapter 1

• Gini impurity: Chapter 3

• Glossary: Glossary

• GridSearchCV: Chapter 2

• GroupKFold: Chapter 2

• Graph structure: Chapter 5

H¶

• Handoff documents: Chapter 15

• Hot-deck imputation: Chapter 7

• Hybrid human-LLM workflow: Chapter 12

• Hyperparameter tuning: Chapter 2

I¶

• Impact gap: Chapter 10

• Imputation: Chapter 7

• Intraclass correlation: Chapter 5

K¶

• KFold: Chapter 2

• K-means: Chapter 6

L¶

• Laplace mechanism: Chapter 9

• Large language models: Chapter 12

M¶

• MCAR/MAR/MNAR: Chapter 7

• Mean imputation: Chapter 7

• Membership inference attacks: Chapter 10

• MLP (multilayer perceptron): Chapter 4

• Model cards: Chapters 8, 14

• Model inversion attacks: Chapter 10

• Model supply chain security: Chapter 11

• Model version pinning: Chapter 12

• Multi-head attention: Chapter 11

• Multiple imputation: Chapter 7

N¶

• NASS data lab: Chapter 10

• Neural networks: Chapter 4

• NIOCCS: Chapter 11

• NIST AI 600-1: Chapter 14

• NIST AI RMF: Chapter 14

O¶

• Observe-decide-act-check loop: Chapter 13

• OMB M-25-21: Chapter 14

• Out-of-bag scoring: Chapter 3

• Overfitting: Chapters 2, 3

P¶

• Partial dependence plots: Chapter 4

• PCA: Chapter 6

• Permutation importance: Chapter 2

• pMSE: Chapter 9

• Positional encoding: Chapter 11

• Predictive parity: Chapter 8

• Privacy budget: Chapter 9

• Privacy-utility tradeoff: Chapter 9

• Probabilistic matching: Chapter 5

• Prompt design: Chapter 12

• Prompt versioning: Chapter 12

• Prompt-as-agent: Chapter 13

R¶

• Random forests: Chapter 3

• Record linkage: Chapter 5

• Regression: Chapter 1

• Reproducibility checklist: Chapter 15

• Rubin’s rules: Chapter 7

S¶

• Scree plot: Chapter 6

• SDL (Statistical Disclosure Limitation): Chapter 10

• Seldon: Chapter 15

• Semantic Drift (T1): Chapter 15

• Sequential regression synthesis: Chapter 9

• Session Continuity (SC): Chapter 15

• SHAP values: Chapter 3

• Silhouette score: Chapter 6

• Six design principles (agentic AI): Chapter 13

• SLMs (small language models): Chapter 11

• Soundex: Chapter 5

• Specification gap: Chapter 10

• State Coherence (SCoh): Chapter 15

• State Discontinuity (T5): Chapter 15

• State Fidelity Validity (SFV): Chapter 15

• State Provenance (SP): Chapter 15

• State Supersession Failure (T4): Chapter 15

• Stochastic regression imputation: Chapter 7

• StratifiedKFold: Chapter 2

• Stratification: Chapter 6

• Subgroup accuracy decomposition: Chapter 8

• Supervised learning: Chapter 1

• Synthetic data: Chapter 9

T¶

• Temperature (LLM): Chapter 12

• Terminological Consistency (TC): Chapter 15

• TEVV: Chapters 14, 15

• Tokenization: Chapter 11

• Tool (agentic AI): Chapter 13

• Transitive closure: Chapter 5

• Transformers: Chapter 11

• t-SNE: Chapter 6

U¶

• UMAP: Chapter 6

V¶

• Validity types (classical): Chapter 15

W¶

• Workflow (agentic AI): Chapter 13