Program · Research

Replication Program

Write and freeze local replication protocols, fork amendments and export the design, analysis rules and review plan.

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Choose a claim from a primary study and fill in the replication planner. State the population, outcome, analysis, exclusions and stopping rule before inspecting the result. Freeze a local version, fork any amendment and export it for independent review or an external registry. This software does not conduct experiments or independently timestamp a preregistration.

Your workspace stays in this browser. Save records, edit them or fork frozen versions, export JSON, a research memo or CSV, and import a backup with an explicit replacement step. Deleting or clearing offers an undo while the page remains open. No notes are submitted to Charitology. The institutional goals below remain the program’s longer-term charter.

What it is

A single study can be informative without settling a question. In 2015 the Open Science Collaboration repeated 100 published psychology studies. Ninety-seven percent of the originals had reported statistically significant results. Only 36 percent of the repeats did. Charitology has not established an equivalent sector-wide rate for charity impact research. That is Open Problem 10, the Replication Rate, and the Replication Program exists to answer it.

How it works

A replication can mean re-analyzing the original data or running the study again somewhere new. The program would do both. It would choose studies by fixed rules, such as how often they are cited and how much money relies on them, and publish the list and the analysis plan before any results come in. Every result would be published, including the ones that hold up.

Charity research has done this before, in public. In 2015 a team re-analyzed an influential 1998–99 school deworming study from western Kenya, using the original data and methods. It was possible because the original researchers shared their data and analysis files. Most results were reproduced. Some were not, including an effect on attendance at nearby schools, for which little evidence remained once coding errors were corrected. The original researchers replied in the same issue of the journal. The program aims for the same openness every time: shared data, published plans and replies printed next to results.

Why it matters for the system

The Silence About Failure applies to research too. A standing program makes re-testing routine, so a finding that doesn’t hold up is published as ordinary news rather than buried or treated as a scandal. It also treats the Measurement Gap from the other side. Measurement helps only if the measurements can be trusted, and replication is how a field learns which ones can.

Risks and limits

A failed replication doesn’t mean the first team did anything wrong. Places change, programs change and chance plays a part. The program would report results without blame and invite the original authors to respond alongside every result.

What success looks like

Within five years, the program has published replications of at least 20 influential findings and an estimate of the replication rate with confidence bounds, and donors can see a replication status next to the studies they rely on.

Choose a claim worth checking

Use the existing intervention register to locate a primary study. Distinguish re-running code from collecting new data, and write the plan before inspecting the result you are testing.

See how a replication can change part of a finding · The replication-rate open problem

Preregistration and replication planner

New record

Freeze a complete, exportable local protocol. To amend it, fork a new draft and record the changes. This planner does not run a study, recruit participants or register a protocol with an external registry.

Your work stays in this browser. Export a backup to move it elsewhere. Entries are your research notes, not verified findings or ratings.

Freeze a version before collecting results. A saved version can be forked, but this workspace does not edit it in place. Browser timestamps are not independent public registration.

Claim and scope
Design
Analysis
Delivery and review
Version record

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Sources

  1. Estimating the reproducibility of psychological science · Open Science Collaboration, Science 349(6251), 2015
  2. Re-analysis of health and educational impacts of a school-based deworming programme in western Kenya: a pure replication · Alexander M. Aiken, Calum Davey, James R. Hargreaves and Richard J. Hayes, International Journal of Epidemiology 44(5), 2015
  3. Commentary: Deworming externalities and schooling impacts in Kenya: a comment on Aiken et al. (2015) and Davey et al. (2015) · Joan Hamory Hicks, Michael Kremer and Edward Miguel, International Journal of Epidemiology 44(5), 2015