🎧audiobooks (fiction and non-fiction)
📚book collections
🗣Learn Hot English (audio)
✅The Economist (audio)
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Created
Between 1 January 2022 and 28 February 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Literature — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (4 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 4 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 18 comparable posts for this entry, running 29 July 2026 to 5 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 2, the earliest publisher we hold is @itsallinenglish. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
34 measurements spanning 53 days, net +462. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 25,912–26,512 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 34
Measured (UTC)
Subscribers
Change
29 Sept 2026, 17:37
26,443
+62
17 Sept 2026, 21:41
26,381
+22
15 Sept 2026, 16:58
26,359
+19
14 Sept 2026, 02:20
26,340
+6
12 Sept 2026, 11:17
26,334
+3
10 Sept 2026, 07:54
26,331
+28
6 Sept 2026, 23:20
26,303
+69
4 Sept 2026, 06:58
26,234
+57
2 Sept 2026, 18:45
26,177
+66
1 Sept 2026, 17:08
26,111
+6
31 Aug 2026, 18:58
26,105
+8
30 Aug 2026, 22:08
26,097
-2
29 Aug 2026, 23:34
26,099
+14
28 Aug 2026, 20:24
26,085
+5
27 Aug 2026, 22:04
26,080
+5
27 Aug 2026, 00:37
26,075
+3
26 Aug 2026, 00:48
26,072
+2
25 Aug 2026, 00:44
26,070
+9
23 Aug 2026, 09:15
26,061
+6
21 Aug 2026, 19:36
26,055
first reading
Engagement
98 posts held, back to 29 July 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 70 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.51%
avg views ÷ 26,443 subscribers
Avg views / post
1,990
35 posts measured
Reaction rate
0.401%
reactions ÷ views · ER floor
Posts in window
35
of 98 held
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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 29 September 2026
Posts held
98 (29 July 2026 – 29 September 2026)
Views total
69,497
Reactions total
279
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
30 Sept 2026, 02:41 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.
What this channel posts
Photos
≈2,080
Videos
≈2
Links
≈1,270
Lifetime counters from Telegram’s own channel header, read 30 September 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.
Video runtime
48s
Average length
12s
Measured directly from 4 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
839 reactions across 98 posts, in 25 distinct kinds. The most used accounts for 57.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
483
57.6%
❤🔥
74
8.82%
👍
53
6.32%
🔥
49
5.84%
👨💻
37
4.41%
👏
36
4.29%
👀
25
2.98%
🙏
18
2.15%
⚡
14
1.67%
👌
12
1.43%
🆒
7
0.834%
😍
7
0.834%
🤝
4
0.477%
✍
3
0.358%
🦄
3
0.358%
🌭
2
0.238%
👎
2
0.238%
🤩
2
0.238%
🤪
2
0.238%
🏆
1
0.119%
5 further kinds
5
0.596%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 98 of the 98 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 839 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 98 most recent posts we hold, published 29 July 2026 to 29 September 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Advertising
Ad load
2.04%
2 of 98 posts carry an ad marker
Regulatory tokens
2
posts carrying an erid · 2 distinct tokens
Median views · ads
2,240
over 2 measured posts
Median views · rest
2,120
over 96 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2W5zFGFYeth
1
23 September 2026
23 September 2026
2W5zFGnegCH
1
10 August 2026
10 August 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 98 most recent posts we hold, published 29 July 2026 to 29 September 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
George Orwell - Animal Farm
Genre: #Classics
A farm is taken over by its overworked, mistreated animals. With flaming idealism and stirring slogans, they set out to create a paradise of progress, justice, and equality. Thus the stage is set for one of the most telling satiric fables ever penned –a razor-edged fairy tale for grown-ups that records the evolution from revolution against tyranny to a totalitarianism ju…
Julieann Campbell - On Bloody Sunday
Genre: #History
The first ever complete oral history of one of the darkest episodes in modern Irish history
🎧📚 To listen to the audiobook:
1. First join our new archive
2. The link to the book is
https://t.me/c/2183543843/4815
〰〰〰〰〰〰〰 〰〰〰〰〰 〰〰
🎧📖 Our audiobook channel
Свежие находки, guys
Просто перейдите и найдите своё!
1. Monkey see, monkey share
Тут все: от фраз для живого общения до истории английского (и про английский). О том, как устроен язык вообще и что с этим делать. Пишет лингвист.
2. Английский для карьеры и жизни 🤩
От B1 к уверенной речи - для работы, конференций и международных возможностей.
3. In лангуаге we trust
Залипательные рассказы про историю слов, мемы и и…
Nikki Erlick - The Measure
Genre: #Science_Fiction
The Measure is a sweeping, ambitious, uplifting story about family, love, hope, and destiny that encourages us to live life to the fullest.
🎧📚 To listen to the audiobook:
1. First join our new archive
2. The link to the book is
https://t.me/c/2183543843/4811
〰〰〰〰〰〰〰 〰〰〰〰〰 〰〰
🎧📖 Our audiobook channel
Ken Liu - The Wall of Storms (The Dandelion Dynasty, Book 2)
Genre: #Fantasy
The second book in The Dandelion Dynasty, the epic fantasy trilogy by Ken Liu.
Dara is united under the Emperor Ragin, once known as Kuni Garu, the bandit king. There has been peace for six years, but the Dandelion Throne rests on bloody foundations – Kuni's betrayal of his friend, Mata Zyndu, the Hegemon. The Hegemon's rule was brutal an…
Ken Liu - The Grace of Kings (The Dandelion Dynasty, Book 1)
Genre: #Fantasy
One of the Time 100 Best Fantasy Books of All Time
Two men rebel together against tyranny—and then become rivals—in this first sweeping book of an epic fantasy series from Ken Liu, recipient of Hugo, Nebula, and World Fantasy awards. Hailed as one of the best books of 2015 by NPR.
🎧📚 To listen to the audiobook:
1. First join our new ar…
⚡️Нейросети уже заменяют носителей языка.
В Telegram быстро набирает популярность ИИ-девушка Chatty, с которой можно голосом практиковать живой разговорный английский и ещё 12 языков на основе новейших моделей искусственного интеллекта. Попробовать можно бесплатно.
🇬🇧 Английский: @ChattyTutorBot
🇩🇪 Немецкий: @ChattyGermanBot
🇪🇸 Испанский: @ChattySpanishBot
🇫🇷 Французский: @ChattyFrenchBot
🇮🇹 Итальянский: @ChattyIta…
Aysegül Savas - The Anthropologists
Genre: #Contemporary
Unfolding over a series of apartment viewings, late-night conversations, last rounds of drinks and lazy breakfasts, The Anthropologists is a soulful examination of homebuilding and modern love, written with Aysegül Savas' distinctive elegance, warmth, and humor.
🎧📚 To listen to the audiobook:
1. First join our new archive
2. The link to the book is
https:…
Ariel Lawhon - The Pirate Queen
Genre: #Historical_Fiction
NEW YORK TIMES BESTSELLER • A sweeping historical adventure inspired by the life of Grace O’Malley, the legendary Irish folk heroine who risked everything to defend her people. Venture onto the high seas with the thrilling latest from the New York Times bestselling author of The Frozen River and I Was Anastasia.
🎧📚 To listen to the audiobook:
1. First joi…
Neal Stephenson - Seveneves
Genre: #Science_Fiction
A writer of dazzling genius and imaginative vision, Neal Stephenson combines science, philosophy, technology, psychology, and literature in a magnificent work of speculative fiction that offers a portrait of a future that is both extraordinary and eerily recognizable. As he did in Anathem, Cryptonomicon, the Baroque Cycle, and Reamde, Stephenson explores some of o…
Сколько лет вы уже учите английский?
Слова знаете, глаголы вроде помните, а говорить и воспринимать речь свободно всё равно не получается?
Пора разобраться, что реально мешает вам перейти на следующий уровень в языке.
Для этого приглашаем на бесплатный вебинар Тани Марковой «3 шага к свободному общению».
На нём разберём:
— какие ошибки тормозят ваш рост в английском;
— как работает система, которая доводит до рез…
🆕 🌺🦋🦋 🌺🦋🦋🦋🦋🦋🦋🦋🦋 – September 26, 2026
🎧 📒 ➖ Audio Edition
The Economist is a global weekly magazine written for those who share an uncommon interest in being well and broadly informed.
Each issue explores the close links between domestic and international issues, business, politics, finance, current affairs, science, technology and the arts. #economist #theeconomist
📌📌📌📌📌
«The Economist» — еженедельный общественн…
❤6👨💻1
Showing the 12 most recent of 98 posts we hold for @thedevilshours. 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.
Posts edited after publishing
@thedevilshours edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
19 August 2026
Most recent edit
19 August 2026
Forward network
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.
Mentions
Named by 2 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
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 29 September 2026 — this
entry's latest reading, not the date you are reading this.
“Muscat Audio books | Аудио книги на английском / The Economist” (@thedevilshours), 26,443 subscribers as measured 29 September 2026. Telegram Register, tgregister.com/channel/thedevilshours.
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.