David Johnston

You could throw a blanket over the top teams in the country netball leagues this season, and that is exactly what makes finals the most exciting time of the year.

Bendigo league flag contender Strathfieldsaye has topped up on the eve of finals with the availability of two VFL-listed players.

At NRF PROTECT 2026, loss prevention leaders discussed how total retail loss helps retailers identify and address risks before they affect profitability

The premiership-winning teams in Gippsland’s seven country footy leagues will be on 36 player points next season, a reduction of two points across all competitions.

Bruthen steamrolled Omeo-Benambra by 61 points to clinch its first Omeo District flag since completing a premiership hat trick in 2019.

Redemption was exacted in thrilling fashion by North Bendigo in downing Mt Pleasant by 11 points in the Heathcote District league grand final at Huntly on Saturday.

Every September, Australians are encouraged to ask someone a simple question: “Are you OK?”

Comment by David Johnston - Regarding question 1: "Uncooperativeness" is sort-of a free parameter here, at least in the way the model functions. If you can build an evaluation whose quality scales sufficiently quickly with AI capability, you can use that as your effective measure of uncooperativeness. I think for the policy feedback aim, credibility and consensus are also really important. So the practical limitation is more about what kind of evaluation pipelines you can build, and what kind of consensus you can build around them. I am personally sympathetic to more ambitious “alignment” targets, but I think consensus is may be a limiting factor on how ambitious you can get. That said, it’s not entirely a free parameter; if you don’t take a stand on traits that are effectively self propagating then you may add a bunch of uncertainty to the self propagation term, which makes the model worse. Similarly if you know a trait undermines your monitoring efforts then not calling it “uncooperative” basically invalidates the broader project. To directly answer your question: yes you distinguish "good cooperativeness" from "bad cooperativeness", "cooperativeness" here is specifically "cooperativeness with the intent to maintain oversight", not "cooperativeness with anything at all". Regarding question 2: Yes, I'm assuming the detector is not becoming less precise (or becoming more precise); I breezily swept that under "regularity conditions". But when I think about answering your question, I wonder if it wouldn't be better to get a sequence of judgement diffs between older and newer detectors, and then you could track the "true positive according to SOTA" and "false positive according to SOTA" trends separately.

Hume league club Billabong Crows has circled October 30 as a crucial date to determine a “clear vision” for its future.