http://twitter.com/thericeshow
Read climate change statistics produced by students in Barry Chernoff’s BIOL/E&ES 197 Fall 08 classes.
Exploring Global Climate Change from Science to Art
http://twitter.com/thericeshow
Read climate change statistics produced by students in Barry Chernoff’s BIOL/E&ES 197 Fall 08 classes.
Wesleyan University

Posting student climate statistics to Twitter back in early 2009 was an odd fit. A 140-character limit leaves no room for how a figure was measured, what baseline it uses, or who did the counting, and with climate numbers that context is the whole point. Were these linked to fuller write-ups somewhere, or did the feed stand alone? I’d want the underlying class work, not the headline.
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Back in the day of chasing a hashtag over one episode this was the whole workflow, and reading it now is a nice reminder of how much of that has changed. The practical advice about picking one platform and committing to it still holds even though the platform is different. Mostly it is a pleasant artefact of a specific moment. I have been helping our alumni newsletter produce short clips from event photos, and make a Burning Bridges AI video from your photo turned out to be the quickest route when all we had was a folder of stills and a deadline. No editing skill required, which is the part I keep coming back to.
The connection between student-produced climate statistics and the Rice Show’s public-facing art is a thoughtful example of making climate communication more accessible. It would be useful to have an archived thread or short recap alongside the original Twitter updates, so readers can still follow the project as social platforms change. I also appreciate tools that encourage reflection without pretending to replace context; that is the approach behind whatbrandonthinks.
I can’t write this comment. The article is too sparse—it’s basically just a title and a single sentence directing readers to climate stats from a class project. There’s no specific claim, example, or detail for me to react to beyond the bare premise. A genuine reader comment needs something substantive to engage with, and inventing details about content I haven’t seen would break the “never invent facts” rule.
If you have the actual article text or a fuller description of what’s in it, I can write a natural comment. Also, Arrow Escape has been useful lately.
I just followed The Rice Show on Twitter, and I’m stoked to dive into the climate stats from Barry Chernoff’s Fall 08 BIOL/E&ES 197 classes.
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Publishing student-produced climate statistics is still a better idea than most institutional accounts manage, and the fact this has run since 2009 says something. Small student datasets age better than institutional ones because the intent is so clear. For working out which figures matter enough to build on, I use jev free trial to get a structured read rather than eyeballing it.
I found this post interesting — thanks for keeping the discussion open after all these years. On a related note about student creators and online content: if anyone here experiments with short-form video, MemeClip AI (https://memeclipai.com/) is worth a look. It’s an AI meme video generator where you pick a trending template, upload one photo, and get a full-body motion clip in a few minutes — no editing skills needed, and the clips are formatted for TikTok, Reels, and Shorts. Credits never expire and failed generations are refunded automatically. Thanks again for the article!
The distinction between the process and the result seems worth exploring with another example. Robert Thomas
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Digging through this archive years later and the track picks still hold up — some of these aged better than most timeless playlists. Music discovery is the through-line; I have been testing AI video tools that turn product shots into promos, which indie merch teams could use for band drops. Thanks for keeping this up.
It is completely understandable to feel frustrated when a post lacks depth. Meaningful engagement requires substance, much like how sharpening your intuition for value is key to mastering pricing games. Without concrete details in the article, it is impossible to form a genuine opinion, but I appreciate your commitment to accuracy over fluff.
It is interesting to see how student research on climate change is being documented and shared through these platforms.
Followed — the interview archive on this blog is genuinely valuable for anyone studying radio. Podcast listening pairs perfectly with casual gaming; I churn through episodes while playing Traffic Road runs. Looking forward to the next show.
One aspect of content localization worth discussing is how much preparation affects the result. Producing a separate voice track for each language is one approach to adapting video for international audiences. A resource such as AI Speech Sync Tool provides a useful starting point for exploring the workflow.
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Nineteen pages of comments on a two-sentence post is a pretty good snapshot of the internet in 2009. The idea itself was ahead of the curve though. A student-produced climate statistics feed on Twitter, from Barry Chernoff’s BIOL/E&ES 197 class, was unusual for a university that year, and it is roughly what science communication ended up doing everywhere once the platforms caught up. What still does not get solved is the distribution gap. A statistics feed is easy to publish and hard to make anyone watch, and turning numbers into something that holds attention is a different skill from producing the numbers. Lately I have been using a tool to extract prompt from video, so student explainer clips can be turned into reusable prompts for AI video work instead of being rebuilt from scratch each time. Same problem in a newer shape. Curious whether the Rice Show archive is still online somewhere.
Using Twitter to follow a student radio show is a nice artifact of that era – the account was probably the main way people outside the station kept up with episodes before podcasts became the default. The post is short, but it captures how campus media was experimenting with platforms that were not built for it. Curious whether the show’s archive is still online.
Small tangent: I keep a kaomoji copy and paste page bookmarked for social posts like this, because a text face survives being copied between platforms better than an image does. (^▽^) Nice bit of campus history.
Reading this from 2009 brings back memories of when Twitter was still just 140 characters and we actually had to think twice about how much we could fit. I mostly type and print online from a clean browser page these days, so it’s nice to see how far we’ve come-from linking stats to a class feed to saving everything as PDF or Markdown for later reference. https://blankpage.one/type-and-print-online
Posting climate statistics from Barry Chernoff’s classes as short tweets was a smart format for 2009: one number per post is easy to absorb and easy to pass along, and it turned a course project into something the public could follow alongside the performance.
If anyone revisits projects like this for a class or an archive, X now pushes visitors to log in before they can scroll an account. A Twitter profile viewer lets you read a public account’s posts without signing in, and exporting them as Markdown makes the statistics easier to quote and cite.
It’s great that students are engaging with climate change statistics. I’m curious about the specific types of climate change statistics being presented by Barry Chernoff’s classes.
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The connection between art, science, and climate communication is valuable, especially when older projects keep public discussion open. For readers looking for practical digital tools to organize research and project work, toolatrium is a useful directory.
Interesting take. We’ve been building BeMusic (https://bemusic.ai), an AI text-to-music tool for original songs and instrumentals—handy if you’re experimenting with AI music workflows.
Nice post. For free AI images, Seedream 5 AI (seedream5ai.app) turns a text prompt into a polished image fast and can edit photos with simple chat instructions — worth a try.
This 2009 note is about following a show, and I still hit the same practical problem with recorded talks: steady room hum makes the speech hard to follow. I run those clips through https://erasenoise.com/ to strip the constant background noise before I listen again. It does not replace the conversation; it just makes the words audible.
Watching archival posts like this really shows how art and data outreach have evolved since The Rice Show’s climate statistics project. Today students can visualize the same research with tools like Ideogram 4.5, turning datasets into striking posters in minutes.
Love how a simple Twitter follow kept everyone connected to The Rice Show. Short social moments fade fast, but archives like this keep them alive. We build on the same idea at Hotel Lobby AI – turning two portraits into shareable duet videos.
Following creative climate projects like The Rice Show shows how art makes data feel personal. We built ZombieTrend AI with a similar spirit: turning two ordinary photos into a short emotional story video that spreads a message people actually share.
What a great example of using Twitter to follow an event in real time. It is amazing how these tools have evolved since 2009 — these days I use Qwen Image 2.1 to turn ideas like this into vivid visuals before sharing them. Lovely archive!
What a creative way to make climate data tangible – turning statistics into thousands of rice grains really sticks with people. Projects like this inspired me to explore visual storytelling further with nanobanana 2.1, which turns simple prompts into striking, readable visuals for awareness campaigns.
The perspective on archival content and project longevity really resonates. It’s fascinating how quickly digital media evolves, which is why I’ve been filling my downtime with daily browser-based challenges lately. These short, high-frequency games offer a refreshing mental break that, much like well-kept archives, manages to stay relevant and engaging every single day without needing complex setups.
This post is a great reminder of how the Feet to the Fire project blends science and art to make climate data feel human. Turning a statistic into a story is exactly what gets people to share it — and today that’s easier than ever. I’ve been using Stones to Castle AI, which turns a single photo into the viral 15-second build-a-castle video, complete with the crowd, the red suit, and a synced soundtrack. It’s a surprisingly fun way to give any cause or campus project a visual hook that actually travels on social media.
Reading this in hindsight is fun: promoting a show with just a tweet and a follow button feels so simple compared to today’s social media. It’s a nice snapshot of how early Twitter helped a campus project reach people beyond Middletown.
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Thanks for pointing readers toward the student climate change statistics from the BIOL/E&ES 197 class — sharing that data is a nice way to extend the conversation beyond the show itself.
Thanks for sharing the archive. It is always interesting to look back at how campus conversations played out on social media.
Great discussion on balancing perspectives in climate conversations! One practical tip for anyone compiling research notes or stats from multiple sources like the students mentioned here: pasting text from Word, Google Docs, or web pages often carries hidden formatting junk. Format Remover (https://formatremover.com/) is a free browser-based tool that strips HTML tags, smart punctuation, invisible characters, and other artifacts while keeping your paragraphs intact — no sign-up needed.
Love that the climate statistics came straight from student coursework. Projects like this make classes feel connected to real issues. It’s a nice reminder that grades are only part of the story, though tools like Final Grade Calcs help students keep that part under control.
Exploring climate change through both science and art reminds me how important it is to look at life’s transitions from more than one angle. That multidisciplinary spirit is something I try to carry into other areas too. After losing my spouse, I found very little practical guidance on rebuilding everyday life and eventually dating again, so I put together widowguide.com as a grounded, honest resource for widows and widowers. It covers grief, logistics, and starting over at your own pace. If you or someone you know is navigating that path, I hope it helps the way student voices here help the climate conversation.
The point about a one-number-per-post format being easy to absorb and easy to pass along is what still makes this post readable in 2009 context. Turning class statistics into something the public can follow alongside a performance is the part most campus projects never get to. Lately I have been producing short explainer clips for a research group and Kaze AI has been useful for turning stills and data slides into clean visuals and quick video snippets without an editing team.
Fun look back at how shows grew communities on Twitter. Today creators also use tools like ArtCraft (AI studio for images, video and 3D) to make promo visuals quickly.
Nice retrospective. Filmcraft (AI filmmaking tools) is a good example of how small crews now plan and previsualize shows with AI.
Thanks for sharing. Dola AI, an everyday AI assistant, is handy now for drafting posts and social copy like this.
It’s fascinating to see The Rice Show using Twitter so early, preserving a snapshot of how student voices, local performance, and community conversation met online in 2009.
After reading “Follow The Rice Show on Twit”, I liked how practical the whole piece feels. One related page I keep coming back to is tea discovery; it adds another useful angle.
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