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 9 September 2026 and assigned it the closest of 31 fixed categories, at 41% 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
37 measurements spanning 64 days, net +68. 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 34,057–34,179 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 37
Measured (UTC)
Subscribers
Change
9 Oct 2026, 06:21
34,165
+62
4 Oct 2026, 18:19
34,103
-25
26 Sept 2026, 19:00
34,128
-16
17 Sept 2026, 10:21
34,144
+11
15 Sept 2026, 12:20
34,133
-1
13 Sept 2026, 21:36
34,134
-4
9 Sept 2026, 21:37
34,138
-3
6 Sept 2026, 15:16
34,141
+5
4 Sept 2026, 05:17
34,136
+12
2 Sept 2026, 18:24
34,124
+9
1 Sept 2026, 17:47
34,115
+2
31 Aug 2026, 20:55
34,113
-8
30 Aug 2026, 23:35
34,121
-1
30 Aug 2026, 00:03
34,122
-1
29 Aug 2026, 03:13
34,123
-1
28 Aug 2026, 04:34
34,124
+6
27 Aug 2026, 06:02
34,118
+3
26 Aug 2026, 04:37
34,115
+6
25 Aug 2026, 03:37
34,109
+5
23 Aug 2026, 20:03
34,104
first reading
Engagement
184 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 119 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.14%
avg views ÷ 34,165 subscribers
Avg views / post
2,440
77 posts measured
Reaction rate
1.06%
reactions ÷ views · ER floor
Posts in window
77
of 184 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 12 October 2026
Posts held
184 (29 July 2026 – 12 October 2026)
Views total
187,870
Reactions total
1,998
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Oct 2026, 22:16 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
≈1,570
Videos
≈78
Links
≈3,760
Lifetime counters from Telegram’s own channel header, read 12 October 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
7m 19s
Average length
1m 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
4,582 reactions across 181 posts, in 49 distinct kinds. The most used accounts for 26.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,234
26.9%
👍
1,004
21.9%
🔥
728
15.9%
🤣
428
9.34%
😁
166
3.62%
👏
150
3.27%
💯
137
2.99%
🤔
117
2.55%
🤡
99
2.16%
🤯
84
1.83%
👎
60
1.31%
😱
49
1.07%
🙈
48
1.05%
🤬
33
0.72%
🤝
23
0.502%
🗿
21
0.458%
😭
19
0.415%
❤🔥
18
0.393%
💔
16
0.349%
😐
15
0.327%
29 further kinds
133
2.90%
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 184 of the 184 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 4,680 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 184 most recent posts we hold, published 29 July 2026 to 12 October 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
15.8%
29 of 184 posts carry an ad marker
Regulatory tokens
29
posts carrying an erid · 29 distinct tokens
Median views · ads
2,280
over 29 measured posts
Median views · rest
2,480
over 155 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. They are printed side by side with the count behind each rather than as a ratio: an ad and an ordinary post are not otherwise matched — for topic, for length, for hour of day — so the gap between them is a description of two groups and not the effect of one being an ad.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2SDnjcoUVhM
1
17 August 2026
17 August 2026
2SDnjd2vrUs
1
1 October 2026
1 October 2026
2SDnjdHdbPh
1
19 August 2026
19 August 2026
2SDnjdLNWzP
1
17 September 2026
17 September 2026
2SDnjdbDmFq
1
28 September 2026
28 September 2026
2SDnjdcumY7
1
27 August 2026
27 August 2026
2SDnjdkaBi3
1
9 September 2026
9 September 2026
2SDnjdyVwEb
1
30 September 2026
30 September 2026
2VSb5xYZeVg
1
1 September 2026
1 September 2026
2VSb5xkMrDx
1
13 August 2026
13 August 2026
2VfnxvbDtGL
1
1 September 2026
1 September 2026
2VfnxxHgM3A
1
8 September 2026
8 September 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. 17 further tokens are held for this entry and not listed here.
Measured over the 184 most recent posts we hold, published 29 July 2026 to 12 October 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.
Топ материалов сентября
Обратите внимание, тональность материалов все более в негатив. Вполне в духе времени. А вот про ИИ мы пишем реже, чем другие каналы. Душа отдыхает, правда?
Тренд на «сдаюсь» - не пора менять сферу?
Где вы сейчас на рынке труда? - результаты опроса нашего канала
70% дерьма - красивый эксперимент, сколько же лишней суеты в работе
HR-стратегия: 10 слайдов, после которых HR выглядит как бизнес…
«Пять дней в офисе, два — удалённо»
После таких объявлений сразу сильней ценишь выходные, правда?
Наслаждайтесь. До завтра еще есть время насладиться
Возможно, скоро кому-то и такая работа покажется не такой уж плохой на фоне других вариантов.
Мы в телеге | Наш канал в макс | Наш канал в VK
📖 Полчаса чтения в день = плюс годы жизни
Сегодня мы празднуем всероссийский день чтения
Дает ли чтение книг преимущество в выживании по сравнению с отсутствием чтения или чтением газет/журналов, и объясняется ли этот эффект когнитивной активностью.
1️⃣Авторы, вузы и год публикации
▪️Avni Bavishi, Martin D. Slade, Becca R. Levy
▪️Yale University School of Public Health
▪️Год: 2016 (Social Science & Medicine)
2️⃣М…
Более трети компаний отказались от годовой премии
Речь не о трети всех компаний.
Заканчивается эпоха, когда премия воспринималась как почти обязательная часть компенсационного пакета.
Исследование «Актион Бухгалтерия», 2026 год.
Выборка: 1076 компаний по всей России.
В 2025 году эти компании выплачивали годовую премию. В 2026-м ситуация изменилась.
36,2% компаний, которые платили премию в 2025 году, отказались от …
Почему молодые в 2025 получают больше, чем возрастные
Комментарии к Даниной (помните такую из HHру? Она была там главным аналитиком по рынку труда. Сейчас она ex-HHру)
Наталья увидела очень интересный факт в данных Росстата:
В 2005 году возраст почти не влиял на зарплату: после 30–35 лет она оставалась практически на одном уровне.
В 2025 году картина изменилась: зарплата достигает пика в 30–35 лет, а затем снижается…
Автоматизация и ИИ больше не в HR-повестке
📊 37,1% работодателей считают автоматизацию без эффекта одной из главных зон неэффективных HR-инвестиций. И только 11,3% ставят её в приоритет. (источник Cnews)
В списке реальных задач: качество найма, производительность и удержание ключевых специалистов.
Показательно, что недостаток автоматизации ограничивает производительность лишь у 9,7% работодателей. Низкая мотивация…
Не успеваете за ИИ-гонкой? Обучите команду ИИ-навыкам быстро и прозрачно на платформе Грейд от Яндекс Практикума
Половина сотрудников в России уже использует ИИ в работе. Но реальный эффект от автоматизации видят те компании, которые внедряют ИИ системно: обучают, отрабатывают реальные сценарии, делятся опытом экспертов.
Попробуйте готовое решение для быстрого обучения команд ИИ-навыкам — Грейд от Яндекс Практикума…
👁 Электронная слежка за сотрудниками: почти не повышает производительность, но заметно повышает стресс
электронный мониторинг сотрудников практически не улучшает результаты работы, зато стабильно увеличивает уровень стресса, а отношение работников к нему зависит от того, насколько открыто и деликатно он используется.
Авторы: Daniel M. Ravid, Jerod C. White, David L. Tomczak, Ahleah F. Miles, Tara S. Behrend.
Вузы:…
Люди перестали увольняться — и это не обязательно хорошая новость
По материалам Форбс
Суть: сотрудник может оставаться в компании, но уже перестать вкладываться в нее.
По данным Gallup State of the Global Workplace 2026, глобальная вовлеченность сотрудников упала до 20% — минимум с 2020 года. Особенно заметно падение среди руководителей: с 31% до 22% за последние три года.
Одновременно набирает популярность термин …
🗓 Вебинар для HR-директоров и руководителей кадровых отделов
Как посчитать окупаемость внедрения КЭДО и не ошибиться с выбором
КЭДО снижает риски судебных исков, упрощает коммуникацию с сотрудниками даже в крупных распределённых компаниях и экономит время HR-отдела. Разберём, как перейти на него с выгодой для компании и без стресса для отдела.
🗓 14 октября ⏰ 11:00 💻 Онлайн
Программа:
🔹 Вячеслав Пустовой, директор…
Ритуалы vs Инструменты HR
Я уже несколько раз противопоставлял в своих постах эти термины.
Иррациональный HR - тренд 2025? - про ритуалы.
Складывается ощущение, что бизнес / HR теряет надежду решить кадровые задачи прямыми, понятными, логичными методами (ну проблема найма персонала никуда не делась, кандидатов на рынке не стало сильно больше, а рекрутинг падает) и начинает обращаться к «танцам с бубнами».
HR-тренды…
Динамика индексов производительности труда и реальной заработной платы
Не очень веселая картина: рост реальной зарплаты систематически опережает рост производительности труда.
Акцентирую: реальной, а не номинальной зарплаты. Т.е. мы якобы становимся богаче. И это не значит, что Росстат врет. Это может объясняться (частично) выплатами сво. Частично повышением зарплат дефицитным профессиям.
«Мы чужие на этом празднике …
💯6❤5👎3🤯2😱2👍1
Showing the 12 most recent of 184 posts we hold for @hranalitycs. 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
@hranalitycs edited 3 posts 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
16 August 2026
Most recent edit
25 September 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 26 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 3 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
WTF_HR @WTF_HR · 19,284 Telegram ranks this channel #1 of 99 here — alongside 98 others — read 2 October 2026
Авито Работа @avito_jobs · 21,383 Telegram ranks this channel #7 of 97 here — alongside 96 others — read 23 September 2026
HR[хаб]вакансии @hrhubvacancy · 22,623 Telegram ranks this channel #7 of 100 here — alongside 99 others — read 20 September 2026
topcareer @topcareerschool · 23,338 Telegram ranks this channel #7 of 100 here — alongside 99 others — read 18 September 2026
Пригодится! 🍎 Библиотека для HR @savetoreadlater · 22,166 Telegram ranks this channel #14 of 100 here — alongside 99 others — read 21 September 2026
The Future Of Work @thefutureofwork · 20,692 Telegram ranks this channel #16 of 99 here — alongside 98 others — read 26 September 2026
Управление персоналом | hr, карьера, кадры @secrets_hr · 22,189 Telegram ranks this channel #18 of 93 here — alongside 92 others — read 22 September 2026
Надежда в HR @NadezhdaHR · 19,736 Telegram ranks this channel #26 of 91 here — alongside 90 others — read 30 September 2026
В найме норм! @Vnaime_norm · 80,733 Telegram ranks this channel #26 of 94 here — alongside 93 others — read 18 August 2026
Кадровику @kadroviku · 45,068 Telegram ranks this channel #35 of 93 here — alongside 92 others — read 27 August 2026
hh.ru @hh_ru_official · 90,317 Telegram ranks this channel #37 of 83 here — alongside 82 others — read 10 September 2026
DigitalHR (ДиджиталлЭйчАр): работа | вакансии | рекрутинг | стартапы @digital_hr · 31,736 Telegram ranks this channel #42 of 100 here — alongside 99 others — read 6 September 2026
Skolkovo School of Management @skolkovo_channel · 43,372 Telegram ranks this channel #46 of 100 here — alongside 99 others — read 28 August 2026
Академия Эдюсон (Eduson) @edusondaily · 20,207 Telegram ranks this channel #48 of 96 here — alongside 95 others — read 28 September 2026
ЭКСЕЛЬХАК @excelhackru · 73,542 Telegram ranks this channel #49 of 87 here — alongside 86 others — read 19 August 2026
Живое обучение @prolearning · 20,714 Telegram ranks this channel #51 of 100 here — alongside 99 others — read 26 September 2026
REFORUM @reforum · 18,863 Telegram ranks this channel #58 of 100 here — alongside 99 others — read 5 October 2026
Я Топ @i_top_groups · 18,780 Telegram ranks this channel #61 of 100 here — alongside 99 others — read 5 October 2026
СберУниверситет @sber_university · 24,150 Telegram ranks this channel #64 of 100 here — alongside 99 others — read 17 September 2026
Зайдите в кадры! @kadrovoedelojournal · 30,818 Telegram ranks this channel #73 of 100 here — alongside 99 others — read 6 September 2026
TOP LEVEL JOB [топ вакансии для руководителей] @toplevel_job · 20,611 Telegram ranks this channel #74 of 100 here — alongside 99 others — read 26 September 2026
Рабочие лайфхаки: секреты и советы @lifehackoftheday · 25,731 Telegram ranks this channel #75 of 97 here — alongside 96 others — read 13 September 2026
Get IT @Getitrussia · 21,423 Telegram ranks this channel #97 of 97 here — alongside 96 others — read 24 September 2026
This channel appears in 23 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 9 October 2026 — this
entry's latest reading, not the date you are reading this.
“HR-аналитика” (@hranalitycs), 34,165 subscribers as measured 9 October 2026. Telegram Register, tgregister.com/channel/hranalitycs.
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.