Thank you Iyan, the pleasure is all mine, it’s such a privilege to have you on the team!

Thanks all for the kind words! Many apologies for the delays, as you may have guessed I’m currently swamped with misc commitments. I’m collecting all feedback in preparation for a further analysis pass sometime in March, so all your suggestions are much appreciated. I’m particularly interested in your suggestions about how to safeguard the analysis: for an observational study like this, it’s important to measure carefully, and to take into account any confounding factors that may introduce a systemic bias in outcomes.

Marion Barry: I’m including both automated messages (required when rejecting a task) and manual @mentions, but only consider messages that have been sent by a validating user at the time of validation. I ‘m not currently considering whether people actually read the message, but agree that it would be a good addition; it can increase our confidence in the causal link.

Tallguy – I agree, this seems to be a good summary: “there needs to be a message”.

BushmanK: yes, this is about HOT contributors only, I do not observe OSM activity outside of HOT. I edited the intro to make it clear that I’m talking about HOT. It’s feasible that the OSM community might operate quite differently; it’s also likely a much more complex space than HOT.

tekim – correct, I don’t go into detail in the short writeup above, but I see that many mappers don’t return after their first contribution, and likely never see any messages. As you suggest, this introduces a potential for confounding factors, which I try to address by introducing a set of carefully selected control variables that can serve as broad proxies for a propensity to remain engaged. Please let me know if you have ideas for other factors to control for. However, this is still only an observational study, and there is a risk that we identify spurious causes. We would have to run experiments to confirm these relationships.

mapeadora – interesting, thanks for these examples! I appreciate when people share such stories, because currently I don’t think many people have reflected very deeply about the contributor experience from this side. Everyone’s experiences will be different, but the sharing of personal experiences helps a lot to make our understanding of the process more concrete.

tekim – I’ve seen some validators use OSM direct messages in addition to TM messages; unfortunately I don’t have access to OSM DMs, so can’t include them in the analysis.

Jorieke – intriguing thought! There definitely are different “styles” of validation, but so far I’ve not compared their impact; in part because we might not yet have enough observational data available for such a fine-grained analysis. Maybe in another 1-2 years… :)

Thanks Tyler! I’m looking forward to the next TM as well :) The design discussions around it are definitely moving in the right direction!

Thanks Nate! Yes I thought I should start sharing these before the TM3 team starts committing to specific goals…

tyr_asd: ah, a very good point. I added a paragraph to the end of the labelling section to explain the statistical method. Please let me know if it’s still unclear; I guess I initially left it out because it’s quite hard to avoid using overly technical language when explaining it. (Maybe someone else has a better way of expressing it?)

RebeccaF: Thank you! Yes, I don’t go into the details here, but I found that the effect of feedback diminishes with each additional day of delay; this is independent of the kind of feedback that is given. Luckily, these days most feedback arrives quickly: as I mention above, 50% of all feedback was given within 28 hours. I expect that with our maturing validator community, this will get even quicker over time. Please let me know if that didn’t clarify it!