Our Commitment

At Axiom, we are focused on producing careful, neutral, and methodologically rigorous insight. Our work is designed to move beyond surface-level measurement to capture nuance, internal tension, and real-world tradeoffs that shape public beliefs and decisions.

We believe good research starts with good questions. Rather than sorting people into simple categories, we design instruments that explore priorities, constraints, and competing values to better understand how people actually feel.

Our goal is to produce clear, defensible findings that decision-makers can rely on.

Meet the Founder

Axiom Analytics is an independent public opinion and survey research practice led by Reg Manzer, a research and evaluation professional working in innovation, implementation, and evidence-informed decision support.

Research Credentials & Ethics

  • TCPS-2 Certified

  • Graduate Researcher (Dalhousie University)

  • Evaluation Methodology Certified (Simon Fraser University)

  • CRIC / ESOMAR Principles Aligned

Our Approach

Axiom Analytics is committed to conducting research in a manner consistent with recognized Canadian and international research ethics and practice standards.

Our work is designed to align with the principles reflected in the Canadian Research Insights Council (CRIC) code and ESOMAR research standards, including:

  • respondent confidentiality and data protection

  • voluntary participation

  • transparency of purpose

  • non-deceptive research practices

  • clear disclosure of methodology where appropriate

  • respectful treatment of participants

All human-participant research activities are guided by TCPS 2 ethical principles.

Methodology

Transparency supports trust — and trust supports good research.

Research Design Principles

Neutral Question Framing

  • Minimize leading language and partisan framing

  • Balanced statements

  • Counter-positions to reduce bias

Nuance-Oriented Measurement

  • Use scaled, conditional, and tradeoff-based questions

  • Consider context & constraints effect on responses

Clarity Over Complexity

  • Understandable and accessible language

  • Avoid jargon and double-barreled questions

Analysis

Our analysis emphasizes:

  • Transparent assumptions

  • Appropriate use of descriptive and inferential statistics

  • Subgroup analysis where sample size supports it

  • Careful interpretation of margins of error and uncertainty

  • Distinction between statistical signal and noise

Where research is shared publicly we aim to disclose:

  • Sample size, method, and weighting

  • Field dates

  • Question wording

  • Sponsor (if applicable)