💡
EA market testing (public)
  • Introduction/overview
    • Introduction & explanation
    • 👋Meet the team
    • 📕Content overview
    • Progress/goals (early 2023)
      • EAMT progress & results
      • Goals, trajectory, FAQs
  • 🤝Partners, contexts, trials
    • Introduction
    • Giving What We Can
      • Pledge page (options trial)
      • Giving guides - Facebook
      • Message Test (Feb 2022)
      • YouTube Remarketing
    • One For the World (OftW)
      • Pre-giving-tues. email A/B
        • Preregistration: OftW pre-GT
    • The Life You Can Save (TLYCS)
      • Advisor signup (Portland)
    • Fundraisers & impact info.
      • ICRC - quick overview
      • CRS/DV: overview
      • 📖Posts and writings
    • University/city groups
    • Workplaces/orgs
    • Other partners
    • Related/relevant projects/orgs
  • 🪧Marketing & testing: opportunities, tools, tips
    • Testing Contexts: Overview
    • Implementing ads, messages, designs
      • Doing and funding ads
      • Video ads/Best-practice guidelines
      • Facebook
      • Targeted ad on FB, with variations: setup
    • Collecting outcome data
      • Facebook ads interface
        • Pivot tables
      • Google analytics interface
      • Google A/B, optimize interface
      • Reconciling FB/GA reports
      • Survey/marketing platforms
    • Trial reporting template
  • 🎨Research Design, methodology
    • Methods: Overview, resources
    • "Qualitative" design issues
    • Real-world assignment & inference
      • Geographic segmentation/blocked randomization
      • Difference in difference/'Time-based methods'
      • Facebook split-testing issues
    • Simple quant design issues
    • Adaptive design/sampling, reinforcement learning
    • 'Observational' studies: issues
    • Analysis: Statistical approaches
  • 🧮Profiling and segmentation project
    • Introduction, scoping work
    • Existing work/data
      • Surveys/Predicting EA interest
      • Awareness: RP, etc.
      • Kagan and Fitz survey
      • Longtermism attitudes/profiling
      • Animal welfare attitudes: profiling/surveying
      • Other data
    • Fehr/SOEP analysis... followup
      • Followup with Thomas Ptashnik
    • Further approaches in progress
      • Profiling 'existing traffic'
  • 📋(In)effective Altruistic choices: Review of theory and evidence
    • Introduction...
    • The challenge: drivers of effective/ineffective giving
      • How little we know...
    • Models, theories, psych. norms
    • Tools and trials: overview
      • Tools/interventions: principles
      • Outcomes: Effective gift/consider impact)
        • (Effectiveness information and its presentation)
        • (Outcome: Pledge, give substantially (& effectively))
          • (Moral duty (of well-off))
        • Give if you win/ conditional pledge
      • Academic Paper Ideas
  • Appendix
    • How this 'gitbook' works
      • Other tech
    • Literature: animal advocacy messaging
    • Charity ratings, rankings, messages
    • "A large-scale online experiment" (participants-aware)
  • Innovationsinfundraising.org
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  1. Profiling and segmentation project
  2. Existing work/data

Kagan and Fitz survey

PreviousAwareness: RP, etc.NextLongtermism attitudes/profiling

Last updated 2 years ago

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Sample, Design, & Measures. We recruited a national online sample of 530 Americans. Participants read and reflected on an introduction to evidence based giving, and then completed our main outcomes of effective giving. Participants then completed a series of measures of their beliefs, behaviors, values, traits, sociodemographics, etc. The instrument, measures, and data are available upon request.

  • Was this a 'representative sample'? How were they recruited?

  • Note they 'read about EA first' ... perhaps making them vulnerable to demand effects?

  • DR: I've requested this data, but I think the authors are having trouble finding the time to dig this up

Primary Measures. To measure effective giving, we assessed several attitudes and behaviors; this summary presents results from a novel 7-item scale, the Support for Effective Giving scale (SEGS) [ ⍺ = .92], and an effective giving behavior allocation.

The items in SEGS assess general interest, desire to learn more, support for the movement, and willingness to share information with others, identify as an effective altruist, meet others who support the movement, and donate money based on effective giving principles. To approximate giving behavior, we presented participants with short descriptions of three causes Deworm the World Initiative, Make a Wish Foundation, and a local high school choir and had them allocate $100 between these groups and/or keeping it themselves.

  • Was the allocation purely hypothetical or incentivized in some way, perhaps 'one response was chosen'?

Secondary Measures.

To measure beliefs, behaviors, and traits of people who endorse effective giving, we employed measures of: perceived social norms, charitable donation beliefs and behaviors, self perceptions, empathy quotient ( EQ ) , empathic concern & personal distress ( IRI ), the five moral foundations ( MFQ 20 ) , the five factor personality model ( TIPI ), goal & strategy maximization ( MS S ), updated cognitive reflection tests ( CRT ), sociodemographics (e.g., age, gender & racial identity, income), politics & religion, familiarity with ‘the effective altruism ’ movement , and state residence

So far, the best overall model predicts 41% of the variance in support for effective giving.

Summarized in posts...

.... After participants read a general description of EA, they completed measures of their support for EA (e.g., attitudes and giving behaviors). Finally, participants answered a collection of questions measuring their beliefs, values, behaviors, demographic traits, and more.

The results suggest that the EA movement may be missing a much wider population of highly-engaged supporters. For example, not only were women more altruistic in general (a widely replicated finding), but they were also more supportive of EA specifically (even when controlling for generosity). And whites, atheists, and young people were no more likely to support EA than average. If anything, being black or Christian indicated a higher likelihood of supporting EA.

Moreover, the typical stereotype of the “EA personality” may be somewhat misguided. Many people – both within and outside the community – view EAs as cold, calculating types who use rationality to override their emotions—the sort of people who can easily ignore the beggar on the street. Yet the data suggest that the more empathetic someone is (in both cognition and affect), the more likely they are to support EA. Importantly, another key predictor was the psychological trait of ‘maximizing tendency,’ a desire to optimize for the best option when making decisions (rather than settle for something good enough).

🧮
TBD - The Life You Can SaveThe Life You Can Save
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Understanding Effective Givers.pdfDropbox
The main report
To Grow a Healthy Movement, Pick the Low-Hanging Fruit - EA Forum
Kagan (and Fitz) study
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