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Channel

Виртуальная библиотека

@arche_library

On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry

507subscribers

+20 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002238881731
TypeChannel
Username@arche_library
CreatedBetween 1 June 2024 and 30 September 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 October 2026
Last confirmed live11 October 2026
Measurements held8
Confirmed unchanged1 time, most recently 11 October 2026
On Telegramt.me/arche_library

Topic

Education — 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 7 October 2026 and assigned it the closest of 31 fixed categories, at 79% 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.

Growth

4875074977 August 2026 — 487 subscribers23 August 2026 — 488 subscribers30 August 2026 — 493 subscribers9 September 2026 — 494 subscribers17 September 2026 — 490 subscribers1 October 2026 — 503 subscribers7 October 2026 — 503 subscribers11 October 2026 — 507 subscribers7 August 202611 October 2026
8 measurements spanning 65 days, net +20. 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 484–510 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Oct 2026, 17:00507+4
7 Oct 2026, 15:23503no change
1 Oct 2026, 13:38503+13
17 Sept 2026, 03:16490-4
9 Sept 2026, 02:18494+1
30 Aug 2026, 12:04493+5
23 Aug 2026, 02:17488+1
7 Aug 2026, 22:19487first reading

Engagement

10 posts held, back to 30 January 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 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
47.3%
avg views ÷ 507 subscribers
Avg views / post
240
3 posts measured
Reaction rate
3.47%
reactions ÷ views · ER floor
Posts in window
3
of 10 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
WindowRolling 30 days · latest post in window 25 September 2026
Posts held10 (30 January 2026 – 25 September 2026)
Views total720
Reactions total25
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Oct 2026, 15:23 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

125 reactions across 10 posts, in 5 distinct kinds. The most used accounts for 55.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥6955.2%
👍3729.6%
❤1310.4%
✍32.40%
👏32.40%

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 10 of the 10 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 125 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 10 most recent posts we hold, published 30 January 2026 to 25 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.

Recent posts

25 Sept 2026, 15:39 UTC115 views9 reactionsread 7 October 2026
Forwarded from @traditionalismPhoto

Новый курс - это 15,5 часов интеллектуального путешествия по сложным настроениям потрясений, которые переживает человек в современную эпоху: тоска, отчуждение, депрессия, тревога, страх смерти, утрата смысла жизни и многие другие. В компании из сотен художников всех эпох и десятков философов, исследователей, писателей и поэтов. В доступном и наглядном формате из 9 лекций. Все цифры и подробности курса в слайдах и н…

🔥7✍1👏1

25 Sept 2026, 15:39 UTC193 views7 reactionsread 7 October 2026

Недавно Евгений Нечкасов завершил работу над новым курсом лекций «Настроения потрясений». Этот курс посвящён состояниям, возникающим в результате взаимодействия человека с современной культурой. Депрессия, апатия, отсутствие воли, тоска, преодоление страха смерти и жизнестойкость — вот основные темы данного курса. Но вместе с ними и глубокая рефлексия, и захватывающее путешествие в мир архаики, искусства, культуры, …

🔥5✍1❤1

15 Sept 2026, 08:45 UTC412 views9 reactionsread 7 October 2026

Дружественный проект, посвящённый метафизику и философу Ананда Кумарасвами, возобновил свою работу после длительной паузы. 📖 Подписывайтесь, друзья: https://t.me/coomaraswamy

❤4🔥3👍2

8 Jul 2026, 06:01 UTC700 views8 reactionsread 7 October 2026
Forwarded from @traditionalismPhoto

Господа, возможность попасть в фокус-группу нового курса лекций открыта в июле и августе. Курс посвящен настроениям потрясений в культуре, в академическо-популярном формате: на стыке философии, психологии, антропологии и культуры, с большим акцентом на произведения искусства, поэзию и язык. От традиционной архаики до Постмодерна. Сейчас мы приближаемся к медиане всего лектория и уже доступные следующие темы: №1: Вр…

🔥6❤1👏1

18 Feb 2026, 09:19 UTC≈1,320 views16 reactionsread 7 October 2026

«Структуры сакрального», Евгений Нечкасов Концентрация базы по мифологии и мифологическому мышлению. В книге разбираются важные понятия и оппозиции (такие как Единое и множественное, хаос, аутентичное, дух, душа и многое другое). Книга содержит в себе материалы курса «человек и священное», который мы уже публиковали ранее. Также в основу книги легли другие важные лекции автора, которые не были опубликованы здесь. …

🔥16

14 Feb 2026, 11:31 UTC≈1,320 views17 reactionsread 7 October 2026
File

File, posted without a caption

👍9🔥7❤1

14 Feb 2026, 11:31 UTC≈1,260 views27 reactionsread 7 October 2026
Photo

Курс лекций по Мартину Хайдеггеру В этих 4 лекциях А. Г. Дугин разбирает философию Мартина Хайдеггера. В первых трех лекциях Дугин просто разбирает онтологию Хайдеггера как преподаватель, не включая в рассказ свои собственные идеи. А вот в четвёртой лекции он излагает свою собственную концепцию daseyn. В целом, это одно из лучших учебных пособий по Мартину Хайдеггеру. Советую слушать, по крайней мере, первые три л…

👍20🔥7

31 Jan 2026, 10:21 UTC≈1,220 views13 reactionsread 7 October 2026
File

Лёд и иное Старая беседа Евгения Нечкасова. Про искренность. Идентичность, ощущение заброшенности в мир и нетождество с современным миром. 0:30 — Два принципа зажжения огня 5:40 — Почему возвращение назад невозможно? 9:10 — Что общего между нами и миром традиции? 11:30 — О будущем: стремление в радикально иное 19:10 — Как помыслить радикально иное? 26:00 — Искренность. Зов бытия 32:20 — Ностальгия по месту, в котор…

🔥6❤5✍1👏1

Showing the 10 most recent of 10 posts we hold for @arche_library. 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

Republishes

Channels on the register whose posts this channel has forwarded.

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 1 registered channel — 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 11 October 2026 — this entry's latest reading, not the date you are reading this.

“Виртуальная библиотека” (@arche_library), 507 subscribers as measured 11 October 2026. Telegram Register, tgregister.com/channel/arche_library.

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.