Climate Policy Organizations Editing and Proofreading Services

A policy brief claims that a proposed carbon pricing scheme "will reduce emissions by 30% by 2035." A legislator's staffer reading this has no way to know whether that figure assumes the policy passes exactly as drafted, whether it depends on complementary measures that are not actually part of the bill, or whether it is one output among a range the modelling produced, because the number is presented as a conclusion with the scenario and assumptions behind it left in a technical appendix nobody attached to the brief.

We edit what climate policy organisations produce to communicate a projected policy impact — policy impact projections and their stated assumptions, modelling scenario and sensitivity disclosures, comparison content against alternative policies, briefing material for legislators and staff, and the correspondence responding to a question about how a specific projection was produced. Our editors work on the number that has to survive being repeated by someone who did not build the model behind it.

The disclosed modelling assumption is what a policy impact figure actually needs attached to it, and its failure is a projection presented as a fact when it is actually the output of a specific scenario with specific assumptions that were never stated alongside it. Will reduce emissions by 30% describes an outcome; it does not describe what the model assumed about implementation timing, compliance rates, or complementary policy, and a reader repeating the figure without that context is repeating more certainty than the number actually supports. We work through these so the core assumptions behind a projection are stated alongside the headline figure, since a legislator's staffer citing this number needs to know what it assumes about the policy actually being implemented as modelled, not discover the assumptions only if they read an appendix; so the range of outcomes the modelling produced is disclosed, not only the central estimate, given that a single number presented alone implies a precision the underlying analysis rarely actually has; so any dependency on measures outside the specific bill being discussed is named explicitly, because a projection that assumes a complementary policy not included in the current proposal is describing a different, larger package than the one actually being debated; so the modelling source and method are cited specifically, given that a reader comparing this projection against a competing analysis needs to know whose model produced each number and how; so a comparison to an alternative policy states what basis the comparison uses, rather than a general claim that one approach is more effective; and so a specific question about how a projection was produced receives the actual scenario and assumptions, not a repetition of the headline percentage. Briefs written this way survive being quoted by someone who was not in the room when the modelling was done.

Everything you send is treated in confidence, including modelling data, policy analysis and stakeholder correspondence. We are editors rather than policy analysts, economists or climate modellers, and we offer no view on modelling methods, policy design or projected outcomes. What we can do is make sure the number carries its assumptions with it.