The course-wide rules for late work, extensions, academic integrity and getting help.

Late work and extensions#

If you expect to miss a due date, contact the convenor before it passes.

Academic integrity#

An estimate is only as good as its disclosed assumptions. A central integrity requirement in this course is making borrowed evidence, proxy data and methods visible: if a published figure, a proxy dataset or somebody else’s method is doing work in your assessed reasoning, say so and say where it came from. You are assessed on transparent reasoning and honest provenance, not on landing near a preferred number.

Use of AI tools#

You may use AI tools while working through the course. You remain responsible for verifying every claim, source and assumption they produce — an AI’s confidence is not evidence. Disclose meaningful AI assistance in your assessed reasoning: what you asked for, and what you kept.

Getting help#

Ask during your tutorial first. Email your tutor when a question can’t wait until the next one; email the convenor for anything course-level rather than specific to your own work.