Science — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 38% 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 the other topics.
Growth
23 measurements spanning 92 days, net -13. 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 5,771–5,814 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 23
Measured (UTC)
Subscribers
Change
6 Nov 2026, 03:30
5,796
-2
3 Nov 2026, 01:06
5,798
+7
31 Oct 2026, 07:46
5,791
-2
28 Oct 2026, 11:27
5,793
+1
25 Oct 2026, 01:07
5,792
+2
21 Oct 2026, 20:51
5,790
-2
18 Oct 2026, 05:31
5,792
-2
15 Oct 2026, 03:00
5,794
-1
11 Oct 2026, 17:40
5,795
+15
5 Oct 2026, 09:56
5,780
-13
27 Sept 2026, 14:00
5,793
+9
17 Sept 2026, 19:19
5,784
-3
13 Sept 2026, 13:15
5,787
+9
9 Sept 2026, 13:00
5,778
+2
4 Sept 2026, 02:19
5,776
-4
1 Sept 2026, 01:04
5,780
+2
25 Aug 2026, 21:04
5,778
-7
22 Aug 2026, 12:44
5,785
-7
19 Aug 2026, 11:38
5,792
-3
12 Aug 2026, 19:37
5,795
first reading
Engagement
31 posts held, back to 15 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 10 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
45.3%
avg views ÷ 5,796 subscribers
Avg views / post
2,620
14 posts measured
Reaction rate
1.67%
reactions ÷ views · ER floor
Posts in window
14
of 31 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 1 November 2026
Posts held
31 (15 July 2026 – 1 November 2026)
Views total
36,730
Reactions total
613
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
4 Nov 2026, 18:56 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.
Reaction mix
1,410 reactions across 31 posts, in 30 distinct kinds. The most used accounts for 35.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
494
35.0%
😢
149
10.6%
🔥
128
9.08%
❤
120
8.51%
😁
114
8.09%
🤯
96
6.81%
✍
60
4.26%
👏
41
2.91%
🤔
32
2.27%
🤬
25
1.77%
😱
24
1.70%
🥰
22
1.56%
👎
19
1.35%
💯
14
0.993%
💔
12
0.851%
🥴
8
0.567%
🤣
7
0.496%
😡
6
0.426%
🕊
5
0.355%
🗿
5
0.355%
10 further kinds
29
2.06%
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 31 of the 31 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 1,410 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 15 July 2026 to 1 November 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.
Telegram Stars
Stars received
8
across the posts below
Posts paid on
8
of 31 we hold a reading for · 26%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @portoulan. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 31 most recent posts we hold for this entry, published 15 July 2026 to 1 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 1 of 14 posts held from the last 30 days (7.14%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Национальные операции НКВД в регионах.
Абсолютное большинство осужденных в 1937-1938г. репрессировалось по "кулацкому" приказу 00447. Национальные операции проходили чуть менее масштабно, но зато заметно отличались по региональной специализации в виде преобладающего направления в каждом регионе.
В большинстве субъектов европейской части СССР на первом месте репрессированные "поляки", в южных республиках естественны…
Кулацкая операция НКВД по регионам: число репрессированных и смертные приговоры.
В настоящее время высшая мера кажется каким-то исключительным явлением, измеряемым в единицах или десятках случаев на миллион там где она всё еще применяется. В эпоху Большого Террора советское государство за смертным приговором в карман не лезло и из общего числа ~800 тыс. репрессированных в 1937-1938г. "кулаков" к высшей мере приговор…
Сегодня в России день памяти жертв политических репрессий.
Репрессивная кампания в СССР началась с убийства Кирова в 1934г., но террор стал по-настоящему массовым с указа 00447 от 30 июля 1937г. о проведении "кулацкой" операции, затронувшей самые широкие слои населения и счёт уже пошел на сотни тысяч.
В советское время масштабы Большого Террора было принято объяснять перегибами на местах, дескать, региональные орга…
Шедевральная советская картографическая пропаганда о том, как хорошо в стране Советов и как плохо за её пределами.
В СССР, понятное дело, растущий подъём народного хозяйства, а во вражеском окружении — массовая безработица и такой же массовый голод из-за несостоятельности капиталистического хозяйства. Причём по миллиону голодающих как-то нашли даже в Турции и Персии при тогдашнем их населении 12–15 млн.
Всё бы ниче…
Украина и вся европейская часть РИ в 1918г. Переустройство Восточной Европы в объективе центральных держав, всё в соответствии с сентябрьской программой 1914 года по образованию буферных государств на восточных рубежах Рейха.
Карта нарисована австрийским украинским картографом, доцентом львовского университета Степаном Рудницким и напечатана издательством G. Freytag & Berndt в Вене в 1918 году при тогда ещё живой Ав…
В 1915 г., работая над созданием "свободной Украины" германские дипломаты видели возможные границы этой "Украины" вот таким образом.
Публикуется впервые.
Залипательные картограммы по иммигрантам в США за 1820-2010г. в разрезе отдельных стран и регионов.
На протяжении 150 лет в миграционном потоке абсолютно преобладали европейцы, уступив в 1970-х азиатам и латиносам. Интересно, что в США очень мало выходцев из юго-западной Европы - испанцев, португальцев и французов. Но зато в избытке ирландцев, англичан, немцев и и итальянцев.
По характерным пикам точёным на графика…
🇺🇸Канал Old Times
📺Сообщество посвящено жизни, искусству, культуре и эстетике периода расцвета США в ХХ веке.
⚡️Если вам интересен американский дизайн, американские автомобили, американский образ жизни и всё то, чем притягательны американские 30-80-е гг. прошлого века, то это место для Вас!
✅ ПРИСОЕДИНЯЙТЕСЬ
Прибывавшие на новые территории переселенцы вместе с собой часто привозили и привычные топонимы или просто называли новое поселение по региону исхода. Так на картах появилось множество Полтавок, Киевок и прочих Черниговок.
Приплывшие в 1899г. в Приморскую область на переселенческом пароходе эстонцы Лифляндской губернии тоже основали поселение с оригинальным названием Лифляндия. Переехали с одного моря на другое.
Да…
Основу большого переселенческого движения на Восток естественным образом составляли триединые русские из центральных аграрных губерний Российской Империи.
Миграционный поток из европейских национальных окраин за Урал хоть и был значительно меньше чем из Черноземья, но всё же ненулевым. Жители западных губерний так же понемногу включались в процесс освоения территорий, хотя для них конечно более актуальным направлени…
Простой способ классификации регионов Российской Империи по их миграционным устремлениям в виде соотношения неместных уроженцев по переписи 1897г.
В красных губерниях преобладает исходящая миграция, в них число уроженцев других губерний меньше, чем число выехавших за её пределы коренных жителей. В синих соответственно картина противоположная.
На одном краю спектра находится Курская губерния, для которой на 7 выехав…
"Морские" переселенцы на Дальний Восток по данным приморского облстата РИ за 1883-1900г.
Несмотря на то, что сибирские территории осваивались Россией ещё с XVII века, заселение этих огромных и удалённых пространств до строительства Транссиба проходило довольно медленно. Само по себе путешествие через весь континет по рекам и грунтовым дорогам являлось задачей со звёздочкой.
В конце XIX века самым быстрым способом п…
👍34❤11👏5🐳4🔥1
Showing the 12 most recent of 31 posts we hold for @portoulan. 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.
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 8 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
История и истории @historygothy · 20,850 Telegram ranks this channel #39 of 94 here — alongside 93 others — read 25 September 2026
Новости истории и археологии @arch_history_news · 25,026 Telegram ranks this channel #40 of 94 here — alongside 93 others — read 15 September 2026
Data distributor @sterngang · 21,148 Telegram ranks this channel #44 of 90 here — alongside 89 others — read 2 October 2026
Лекторий Dостоевский @dostoevsky_fm_dostoverno · 78,592 Telegram ranks this channel #44 of 91 here — alongside 90 others — read 18 August 2026
Блондинка с укаZкой @proistoriyZ · 24,495 Telegram ranks this channel #47 of 95 here — alongside 94 others — read 15 September 2026
Рецепты для мультиварки @multivar · 27,741 Telegram ranks this channel #65 of 80 here — alongside 79 others — read 10 September 2026
This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“Компас и портулан” (@portoulan), 5,796 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/portoulan.
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.