Other / unclassifiable — 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 22 September 2026 and assigned it the closest of 31 fixed categories, at 87% 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
8 measurements spanning 61 days, net -6. 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 306–314 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
7 Oct 2026, 12:17
307
-3
27 Sept 2026, 17:40
310
+2
14 Sept 2026, 03:15
308
-1
7 Sept 2026, 04:58
309
-1
30 Aug 2026, 10:33
310
-1
23 Aug 2026, 11:54
311
-2
8 Aug 2026, 07:35
313
no change
7 Aug 2026, 17:49
313
first reading
Engagement
19 posts held, back to 23 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 19 posts for this entry, the most recent from 19 March 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
2m 21s
Average length
28s
Measured directly from 5 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
555 reactions across 18 posts, in 8 distinct kinds. The most used accounts for 41.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
228
41.1%
custom 5258115022093060137
97
17.5%
custom 5287621120999040653
56
10.1%
custom 5373212771167009849
42
7.57%
custom 5381815466106840756
39
7.03%
💋
38
6.85%
🔥
32
5.77%
🌭
23
4.14%
Custom emoji. 4 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.
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 18 of the 19 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 555 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 23 January 2026 to 19 March 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
4
across the posts below
Posts paid on
2
of 18 we hold a reading for · 11%
Most on one post
3
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @blacksocio. 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 19 most recent posts we hold for this entry, published 23 January 2026 to 19 March 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.
🤩 ПОЧЕМУ ДЕЛЬТА — ДЕДЫ?
Вайбоник-контент, который вы заслужили.
Принцип дифференциации квадр для меня схож с этапами развития человека.
4️⃣ стадии: детство, юность, взросление, зрелость.
Т. к. эти этапы архетипичны, сочны в определениях и имеют запоминающиеся критерии, можно использовать это как доп. ассоциацию для начинающих в соционике, например, для изучения квадровых ценностей, либо просто как забавную мозгову…
🌟 Нишевые типологии. Часть 1.
Как на твою личность повлияла твоя уретра? Как насчет пометки "хищник" в твоем типологическом паспорте? Сегодня первая часть обзора странных и нишевых типологий.
🌟 Системно-векторная психология. Вылезла из психоанализа. Представляет из себя 8 психологических векторов, проявляющихся в человеческой личности: анальный, оральный, уретральный, кожный, зрительный, слуховой, мышечный, обоняте…
🤩 СОЦИОНИКА ≠ MBTI.
Часто вижу рядом с соционическими типами приписку из MBTI: например," Гексли, ENFP". Видели такое?
Ставить в один ряд эти две типологии, на мой взгляд, некорректно. И вот почему.
🤩Разные цели создания. Авторство соционики, как и самого термина, принадлежит Аушре Аугустинавичюте, литовской экономистке. Женщина вдохновилась не только типологией Юнга, но и теорией информационного метаболизма Кемпинс…
#заботливый #инфантил ?
нет, это #болевая_бс #виктим контролирует свои переносы
❤16custom 52581150220930601377💋4
Showing the 12 most recent of 19 posts we hold for @blacksocio. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
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 7 October 2026 — this
entry's latest reading, not the date you are reading this.
“черная вайбоника” (@blacksocio), 307 subscribers as measured 7 October 2026. Telegram Register, tgregister.com/channel/blacksocio.
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.
