Channel
@mrRSSfeed
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
300subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002200615661 |
|---|---|
| Type | Channel |
| Username | @mrRSSfeed |
| Description | Marginal Revolution posts, reposted here for Telegram. |
| Created | Between 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/mrRSSfeed |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 08:02 | 300 | no change |
| 7 Aug 2026, 13:41 | 300 | first reading |
20 posts held, back to 4 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
| Window | Rolling 30 days · latest post in window 8 August 2026 |
|---|---|
| Posts held | 20 (4 August 2026 – 8 August 2026) |
| Views total | 336 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 08:02 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
*Restoring Childhood: How to Set Kids Free in the Age of Anxiety* Tyler Cowen That is the new book by Peter Gray, and it is very much a whole philosophy of child-rearing and also antidote to the current panic over social media. Excerpt:In preparation for this chapter, I spent weeks poring over the research literature pretaining to smartphones, social media, and teen mental health. It is clear to me that there is so…
What I’ve been reading Tyler Cowen 1. Mike Jay, Wireheads: An Unnatural History of Technology in the Brain. Much of this story is told through the lens of the accompanying science fiction and non-neuro trends in other parts of science. An excellent book, substantive on every page, and it will make you want to read some of the works he cites.2. Vasily Grossman, From the Front Line, Stalingrad-Treblinka-Berlin 1941-…
The Queen song ’39 Tyler Cowen I only recently learned what it is really about, namely very rapid travel into space and time dilation mattering for the return voyage.I had never before listened carefully to the lyrics. I heard the “’39” reference at the beginning, the mention of volunteeers sailing away, and the general nostalgic British music hall mood to the piece, and assumed it concerned the Second World War. …
Friday assorted links Tyler Cowen 1. Denmark fact of the day.2. “Books that Tyler Cowen probably would like.”3. The tenure dismissal of Sanjay Reddy (NYT).4. Dell and Rambachan NBER video on the economics of AI. I have yet to view, but “self-recommending.”5. Anton Leicht on AI and how the concentration of power will evolve. Very good piece.6. Universities would prefer not to.7. Which polities can you really trust?…
AI and Marginal Revolutions in Wastewater Treatment Alex Tabarrok An interesting paper from French economists, including recent Nobelist Philippe Aghion, looks at the savings from a predictive machine-learning model applied to wastewater treatment:This paper studies the environmental effects of a specialised AI aeration-control system deployed across French wastewater treatment plants operated by a global leader in …
My excellent Conversation with Julia Ioffe Tyler Cowen Here is the audio, video, and transcript. Here is from the episode summary:Julia joined Tyler to discuss why so many of Russia’s great constructivist painters were women, why the tsarist government established women’s medical courses in 1872, changing attitudes towards abortion and birth control in the 20th century, why the Soviet regime turned prudish, how Khr…
Solve for the (Refine) equilibrium Tyler Cowen We’re proud to announce that Refine has signed partnerships with two leading publishers in economics. Both the American Economic Association and the Econometric Society now use Refine’s AI-assisted technical verification as part of their publication processes.Here is the thread. And more comments here.The post Solve for the (Refine) equilibrium appeared first on Margin…
Thursday assorted links Tyler Cowen 1. “Next to rising oxygen levels and other contributing factors, the importance of feces in ancient ecosystems is often overlooked…”2. New publication on AI and institutions. Good people involved.3. Chicago boys in Chile.4. What kind of machine can a book make?5. Longevity firms push for medical deregulation in Montana (WSJ).6. OpenAI Economic Research Exchange.7. Victor Niederho…
The Binmen of Birmingham Alex Tabarrok I was on the British CapX Podcast talking about the Equality Act, riffing off my two posts Equality Act 2010 and The Apples and Oranges Tribunal. One thing I discussed in the podcast which I haven’t blogged on is the amazing Birmingham dustbin dispute.In 2010 an employment tribunal ruled that Birmingham City Council had discriminated against thousands of female workers — cooks,…
Will U.S. cities face a knock-on fiscal crisis from the feds? Tyler Cowen Federal money flows to cities in three flavors: direct transfers, indirect transfers, and what we call fiscal dark matter. Direct transfers are exactly what they sound like — money sent directly from the federal government to various localities. These include funds disbursed through programs like the Community Development Block Grant (CDBG), w…
Who Pays for Unions? Tyler Cowen If unions raise worker wages, who pays? We provide a comprehensive assessment of firm responses to increased unionization, using changes in the tax deductibility of union dues in Norway as a quasi-exogenous source of variation in firm-level union density. In the average private sector firm, higher union density raises labor costs and leads firms to contract employment and production,…
Wednesday assorted links Tyler Cowen 1. A catalog of past AI predictions.2. Jasmine Sun on why people do not want data centers. And Jasmine Sun on Ezra Klein, on data centers (NYT).3. A bot running an SF retail boutique? (NYT)4. Elise Cawley, RIP.5. On the NYC grocery store plan.6. New credit card gives you tokens instead of miles.7. Does AI mean the end of math heroes? Some other heroes too?The post Wednesday ass…
Showing the 12 most recent of 20 posts we hold for @mrRSSfeed. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank — 805,521 of 1,481,217entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 8 August 2026 — this entry's latest reading, not the date you are reading this.
“Marginal Revolution Feed on Telegram” (@mrRSSfeed), 300 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/mrRSSfeed.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.