Data, Judgement and Public Value

Reframing data to strengthen leadership practice. This five-part masterclass series examines how data shapes – and is shaped by – public institutions, communities, and systems of accountability.

About the Course

Reframing data to strengthen leadership practice.

This five-part masterclass series examines how data shapes – and is shaped by – public institutions, communities, and systems of accountability. Rather than treating “data” as a neutral or universal concept, the series invites participants to question assumptions, explore alternative framings (such as evidence, knowledge, and story), and understand the cultural, ethical and governance considerations that underpin public value in practice. 

Participants will encounter perspectives spanning data ethics, evidence-informed policymaking, First Nations data sovereignty, organisational capability, and the relational nature of trust in public data use. 

Stefaan Verhulst lectures Session 4 of the Masterclass, for more see below: 

 Data Stewardship with Dr Stefaan Verhulst PHD

Overview:

Building on earlier sessions, this masterclass focuses on what responsible data leadership and stewardship look like in practice. Participants explore how institutions can use data to support learning, sense‑making and public value — rather than false certainty, compliance theatre or narrow optimisation. 

The session emphasises trust, governance and institutional capability over tools and analytics, helping leaders reflect on how performance systems, dashboards and metrics can both support and distort decision‑making. 

Focus areas:

  • Stewardship versus ownership of data.

  • Trust, legitimacy and institutional responsibility.

  • Using data for learning rather than certainty.

  • Designing feedback loops that support public value outcomes.

Wednesday 8 July, Online

  • 12:00pm - 2:00pm (AEST)

  • 10:00am - 12:00pm (AWST)

  • 2:00pm - 4:00pm (NZST)

Learning Objectives

  • Data for Decision Making

  • Public Data Use

  • Learning through Dialogue and Exchange

Expected Outcomes

  • 1

    Stewardship versus ownership of data

  • 2

    Trust, legitimacy and institutional responsibility

  • 3

    Using data for learning rather than certainty

  • 4

    Designing feedback loops that support public value outcomes

Partners

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