Lost Causal
Debunking Myths About Causal Analysis in Philanthropy – With 2024 Prologue
Bibliographic Data
| ID | 12982203 |
|---|---|
| Authors | Jewlya Lynn (corresponding author), Sarah Stachowiak, Julia Coffman |
| Year | 2024 |
| Volume | 16 |
| Issue | 1 |
| Publication date | 2024-06-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Foundation Review (JOURNAL) |
| Journal identifiers | ISSN: 1944-5660 • E-ISSN: 1944-5679 |
| Publisher | Grand Valley State University Libraries - DIGITAL COMMONS JOURNALS (PUBLISHER) |
| DOI | 10.9707/1944-5660.1693 |
| OpenAlex | W4399999063 |
| Language | EN |
| References cited | 7 |
Editor’s Note: This article, first published in print and online in 2022, has been republished by The Foundation Review with minor updates. What if philanthropic evaluations told us that changes in the world had occurred, as well as how and why they occurred, including whether what foundations funded and grantees did contributed to those changes? What if evaluations made change pathways more visible, tested hypotheses and assumptions, and generated new insights based on what happened in the “black box” of systems change strategies? This type of learning comes from causal analysis — inquiry that explores cause-and-effect relationships. Yet currently in philanthropy, particularly for strategies and initiatives that feature high complexity, few evaluations use robust techniques for understanding causality. Instead, philanthropic evaluation tends to rely on descriptive measurement and analysis. These descriptions often are rich, meaningful, and in-depth, but they remain merely descriptions nonetheless. This article challenges the myths that hold us back from causal inquiry, allowing us to embrace curiosity, inquiry, and better knowing, even (or especially) if it means learning that our assumptions and theories do not hold up. We argue that philanthropy more frequently needs to examine causal relationships, using a growing suite of methodological approaches that make this possible in complex systems. Causal methodologies can challenge and strengthen the often uncontested beliefs that underlie philanthropic interventions, while offering evidence about enabling contexts and system drivers. Strong causal analysis considers not only the funder’s model and assumptions, but also the beliefs others hold about how and why change occurs, opening the door to more equitable and less biased ways of understanding change
Archaeology · Causal analysis · Economics · Management · Mythology · Political science · Prologue · Classics · History · Qualitative Comparative Analysis Research
Causal Inference Using Potential Outcomes
Extending the yarning yarn
What’s Race Got to Do With It? Equity and Philanthropic Evaluation Practice
Implications of the Changing Conversation About Causality for Evaluators
Causation
Can You Really Measure That? Combining Critical Race Theory and Quantitative Methods
Evaluation for Models and Adaptive Initiatives
| Highly cited | No |
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