Peer Review Issue Templates

This file contains two review templates: one for the Phase 1 biomass briefing (Week 4) and one for the Phase 2 summative report (Week 10).

Phase 1: Biomass Briefing Review (Week 4)

You will be assigned two classmates’ briefings. File one Issue per briefing. The Issue is a conversation: the author may reply.

Your Verdict and Argues answers are read by a script that builds the class results. Under each of those two headings, write exactly one of the options listed, in capitals.

Check first: on your classmate’s repo, click Issues → New issue. If a Peer review (Week 4) form is offered, choose it: it has drop-down menus for Verdict and Argues, and tick boxes. If not, open a blank Issue, title it Peer review, and copy the block below into it (the copy button is at its top right).

<!-- Text between these arrows is a note: it won't appear in your Issue.
     To tick a box, put an x inside the brackets: - [x]
     Use the Preview tab to check how your Issue will look. -->

### Verdict

FAITHFUL

<!-- Write exactly one of: FAITHFUL / SUSPECT
  FAITHFUL = you believe the author was arguing in good faith.
  SUSPECT  = you believe the author was deliberately misleading you. -->

### Argues

KEEP-ONLY-WITH-CCS

<!-- Write exactly one of: KEEP-OR-EXPAND / KEEP-ONLY-WITH-CCS / PHASE-OUT
  What does the briefing recommend for UK biomass power? Separate from
  whether you trust it. An honest briefing and a traitor's briefing
  can reach the same conclusion. -->

### Clarity

- [ ] The summary states a clear conclusion up front
- [ ] A non-specialist (e.g. a government minister) could follow the
      argument
- [ ] Every figure is referenced in the text

### Comments on clarity

> [Write 1–2 sentences. Is the main message clear? Could the reader
> stop after the summary and still know the answer?]

### Evidence

- [ ] Numbers have context or comparators ("Is that a big number?")
- [ ] Figures are clearly labelled (axes, captions, units)
- [ ] Data sources are cited

### Comments on evidence

> [Write 1–2 sentences. Are the figures well-chosen? Do they support
> the argument? Is anything presented without context?]

### Uncertainty

- [ ] The briefing acknowledges limitations or assumptions
- [ ] More than one scenario or sensitivity is discussed
- [ ] The briefing distinguishes between what is measured and what is
      assumed

### Comments on uncertainty

> [Write 1–2 sentences. Does the author acknowledge that the answer
> depends on assumptions? Are any claims presented as more certain than
> they should be?]

### Why I reached that verdict

**Required — at least two sentences.**

> [Point to specific figures, claims, or omissions. "It just feels
> wrong" is not sufficient.]

### What made me want to believe this

**Required — and answer it honestly even if your verdict is SUSPECT.**

This is the question the class discussion is built on, so write it as
if it will be read aloud, because some of these will be.

> [What did this briefing do *well*? Which sentence, figure or number
> was most persuasive? Did the briefing reinforce / challenge what you
> thought before you started reading?]

### One suggestion for improvement

> [Name one specific thing the author could improve, regardless of
> whether you trust the briefing.]

Instructions for reviewers (Phase 1)

  1. Read the whole briefing first before filling in this template. First impressions matter: note your gut reaction, then look more carefully.
  2. Check the figures carefully. Look at axis ranges, what’s included and excluded, and whether the caption matches what the figure actually shows.
  3. Ask “compared to what?” every time you see a number.
  4. Separate the conclusion from the craft. A briefing can reach the conclusion you personally believe and still be dishonest about how it got there. That is exactly what the Argues field is for.
  5. Be constructive. Even if you think the briefing is from a traitor, your feedback should be useful.

Phase 2: Summative Report Review (Week 10)

Use this template when reviewing a classmate’s policy report. You will be assigned someone from a different project group, so you are evaluating unfamiliar work — just like a real peer reviewer.

Copy the block below into a new GitHub Issue (the copy button is at its top right).

Issue title: Peer review

## Peer Review

### Summary and clarity

- [ ] The summary states a clear finding and recommendation
- [ ] The argument flows logically from question → method → result →
      conclusion
- [ ] A non-specialist policy-maker could follow the report

**Comments on clarity:**

> [Write 1–2 sentences. Is the main message clear from the summary
> alone? Does the report tell a coherent story?]

### Evidence and analysis

- [ ] Statistical tests are appropriate for the data and question
- [ ] Assumptions are checked and documented
- [ ] Effect sizes or confidence intervals are reported (not just
      *p*-values)
- [ ] Figures are well-chosen, clearly labelled, and referenced in the
      text
- [ ] Numbers have context ("Is that a big number?")

**Comments on evidence:**

> [Write 1–2 sentences. Are the analytical choices justified? Is
> anything presented without enough context or support?]

### Uncertainty and limitations

- [ ] The report acknowledges what the analysis cannot tell us
- [ ] Assumptions and potential confounders are discussed
- [ ] The conclusion matches the strength of the evidence (no
      overstatement)

**Comments on uncertainty:**

> [Write 1–2 sentences. Does the author distinguish between what is
> established and what is uncertain? Are any claims stronger than the
> evidence warrants?]

### Reproducibility

- [ ] The methods are described clearly enough to reproduce
- [ ] Code is committed to the repo and runs

**Comments on reproducibility:**

> [Write 1–2 sentences. Could you re-run this analysis from the repo?
> Is anything missing or unclear in the methods?]

### One thing done well

> [Name one specific thing the author did effectively.]

### One thing to improve

> [Name one specific thing the author could change to strengthen the
> report.]

Instructions for reviewers (Phase 2)

  1. Read the whole report first before filling in this template. Get the overall picture, then evaluate the details.
  2. Check the analysis, not just the writing. Look at whether the statistical tests match the data and question. Are assumptions checked? Are effect sizes reported alongside p-values?
  3. Apply the course refrains. “Is that a big number?” “Compared to what?” “What assumptions are we making?” “How plausible was this before we tested?” “What is the model not capturing?”
  4. Be specific and constructive. Point to particular figures, paragraphs, or claims. “The conclusion seems too strong” is less helpful than “The conclusion says X is the dominant factor, but the R² is only 0.35.”
  5. File your review as a single Issue (not multiple). Use the checkboxes and comment sections above.