Ongoing Inquiries & Research Initiatives

Active tracks in AI, psychology, and measurement science—built for evidence and application.

Browse Active Tracks

Research in progress

PrimeStata’s live research stream examines how humans and algorithms make decisions together, how we measure what matters, and how findings translate into usable systems. Each track lists a short abstract, methods, and status so collaborators can plug in quickly.

These inquiries are not a separate destination from consulting work. They help shape AI Strategy, Data Science, and adjacent diagnostics when clients need evidence before scaling a decision.

Active research tracks

The Independent & Interdependent Behavioral Engagement Scale (IIBES)

Status: Active

Developing a multidimensional measure of engagement capturing independent, collaborative, and off-task behavioral dynamics. Emphasis on factor structure, reliability, invariance, and interpretability across teams.

  • Methods: EFA/CFA, α/ω reliability, measurement invariance, multilevel models
  • Artifacts: Scoring guide, norms, interpretation bands
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Human–AI Alignment in Analytical Decision-Making

Status: Recruiting 2026

Studying how human reasoning interacts with ML predictions in business and policy contexts. Focus on trust calibration, interpretability, and ethical transparency in high-stakes environments.

  • Methods: Experiments (A/B), DiD, SHAP/ICE analysis, mixed-methods
  • Artifacts: Model cards, decision logs, alignment heuristics
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Measuring Cognitive Load in Remote Collaboration

Status: In design

Quantifying attention, fatigue, and cognitive resource use during distributed collaboration via short-form psychometrics and multimodal analytics. Goal: indicators teams can act on.

  • Methods: Brief validated scales, time-series, mixed-effects models
  • Artifacts: Team-level dashboards, action heuristics
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Methods & measures

Psychometrics

Construct mapping, EFA/CFA, reliability (α/ω), invariance testing, score bands and norms.

Causal & experimental

A/B and multivariate experiments, difference-in-differences, hierarchical models, uplift/hazard analysis.

Human + AI analysis

Explainable ML (SHAP/ICE), governance artifacts, bias checks, interpretable model reports.

Roadmap

01. Design & preregistration

Hypotheses, instruments, sampling plan, and power analysis.

02. Data & quality

Collection pipelines, checks, documentation, and governance.

03. Analysis

Modeling, effect sizes, uncertainty, and sensitivity diagnostics.

04. Translation

Executive briefs, technical appendices, and operator-ready artifacts.

These active tracks most naturally support AI Strategy when leaders need governed experimentation, interpretable automation, and research-backed adoption logic before broader rollout.

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Turn active inquiry into a scoped engagement

Use these tracks to understand where PrimeStata is pushing methods forward, then bring the relevant decision, team, or implementation question into a consultation.

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