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Channel

ВШГУ Президентской академии

@gspmranepa

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

5,841subscribers

-16 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001555447742
TypeChannel
Username@gspmranepa
Created14 March 2022measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/gspmranepa

Growth

5,8415,8575,8496 August 2026 — 5,857 subscribers6 August 2026 — 5,856 subscribers9 August 2026 — 5,855 subscribers12 August 2026 — 5,841 subscribers6 August 202612 August 2026
4 measurements spanning 6 days, net -16. 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 5,839–5,859 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 11:445,841-14
9 Aug 2026, 16:225,855-1
6 Aug 2026, 10:115,856-1
6 Aug 2026, 06:375,857first reading

Engagement

22 posts held, back to 31 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 9 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
5.49%
avg views ÷ 5,841 subscribers
Avg views / post
320
22 posts measured
Reaction rate
1.88%
reactions ÷ views · ER floor
Posts in window
22
of 22 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. It is computed over the 21 of 22 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 August 2026
Posts held22 (31 July 202611 August 2026)
Views total7,049
Reactions total127
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 03:46 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

Video runtime
2m 36s
Average length
2m 36s

Measured directly from 1 video 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

77 reactions across 13 posts, in 15 distinct kinds. The most used accounts for 23.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍1823.4%
1722.1%
👏1215.6%
🔥1215.6%
🤝33.90%
🥰33.90%
custom 539125594166240739222.60%
22.60%
👌22.60%
custom 521742391352022990211.30%
11.30%
🗿11.30%
😁11.30%
😴11.30%
🙊11.30%

Custom emoji. 2 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 areTelegram’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 21 of the 22 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 127reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 22 most recent posts we hold, published 31 July 2026 to 11 August 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

11 Aug 2026, 10:02 UTC208 views2 reactionsread 12 August 2026
Photo

В Кабардино-Балкарской Республике завершилось обучение первого потока кадровой программы для участников и ветеранов СВО Дипломы о профессиональной переподготовке получили 31 выпускник региональной программы «Герои Кабардино-Балкарской Республики», реализуемой совместно с Институтом ВШГУ. В торжественной церемонии приняли участие первый заместитель Председателя Правительства Кабардино-Балкарской Республики Сергей Го

👍1👏1

11 Aug 2026, 08:10 UTC219 views3 reactionsread 12 August 2026
Photo

🔤🔤🔤🔤🔤 Информационная безопасность — уже не только про технологии За последние несколько лет подход к информационной безопасности (далее – ИБ) в государственном секторе заметно изменился. Нормативные требования всё больше связывают её с системой управления, распределением полномочий и компетенциями руководителей. ➡️Это означает, что руководителям и управленческим командам важно не только выстраивать работу профильны

1👏1🥰1

11 Aug 2026, 06:31 UTC237 views4 reactionsread 12 August 2026
Photo

🔤🔤🔤🔤🔤 среди участников программы «Время героев» Кавалер двух орденов Мужества, участник программы «Время героев» Роман Олешкин назначен заместителем главы Печенгского муниципального округа Мурманской области. 🎓 В июне 2025 года он стал одним из 85 участников второго потока программы «Время героев». Наставником Романа Олешкина на программе выступает губернатор Мурманской области Андрей Чибис. 🏅 За проявленный герои

2👍1👏1

10 Aug 2026, 17:20 UTC297 views8 reactionsread 12 August 2026
Photo

От качества управления в органе власти до кабинета главного врача: как меняется управление российской медициной На прошлой неделе в Уфе, на базе флагманской клиники Башкортостана — РКБ им. Г.Г. Куватова, состоялось знаковое событие для управленцев здравоохранения. Более 60 главных врачей республиканских, областных, краевых и окружных больниц из свыше 40 регионов России собрались обсудить смену управленческой парадиг

4👍2custom 53912559416624073922

10 Aug 2026, 16:40 UTC295 views6 reactionsread 12 August 2026
Photo

🔤🔤🔤🔤🔤 Институт ВШГУ обучает госслужащих из Республики Экваториальная Гвинея Иностранная делегация прибыла в Москву для прохождения обучения программы повышения квалификации «Современные технологии государственного управления» Обучение пройдет на базе Президентской академии. Слушатели посетят Аналитический центр при Правительстве РФ, Ситуационный центр Правительства Москвы и Национальный центр «Россия», а также дост

2🔥2👍1😁1

10 Aug 2026, 07:00 UTC317 views6 reactionsread 12 August 2026
Video

🔤🔤🔤🔤🔤 Превращаем идеи в капитал В стенах ВШГУ Президентской академии завершился первый очный модуль интенсивной программы «Развитие креативной экономики региона» для министров экономического развития регионов, министров культуры, их заместителей и руководителей уполномоченных организаций. Главная задача модуля — запустить процесс трансформации, понимания того, как креативный продукт может изменить «экономику места»

👌2👍2👏1custom 52174239135202299021

10 Aug 2026, 06:03 UTC336 views5 reactionsread 12 August 2026
Photo

В Тамбовской области завершилось обучение первого потока слушателей по программе «Герои Тамбовщины» Дипломы о профессиональной переподготовке получили 27 выпускников региональной кадровой программы для участников и ветеранов СВО. 📣 В торжественной церемонии приняли участие глава Тамбовской области, выпускник первого потока федеральной программы «Время героев» Евгений Первышов, директор ВШГУ Президентской академии О

👍3👏1🥰1

7 Aug 2026, 16:03 UTC325 views5 reactionsread 10 August 2026
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🔤🔤🔤🔤🔤 Регионы изучили транспортный опыт Москвы В столице прошла выездная сессия в рамках программы ВШГУ Президентской академии «Практики качества жизни», реализуемой совместно с Агентством стратегических инициатив и Правительством Москвы Участниками стали представители управленческих команд Республики Северная Осетия — Алания, Республики Дагестан, Хабаровского края, Костромской, Иркутской и Орловской областей. Слу

🔥3👍1👏1

7 Aug 2026, 14:03 UTC286 views10 reactionsread 10 August 2026
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🔤🔤🔤🔤🔤 Завершилось обучение первого потока программы по наставничеству Программа повышения квалификации «Эффективное наставничество на государственной службе» ВШГУ Президентской академии длилась пять дней. Ее участники — федеральные государственные гражданские служащие, руководители и специалисты, которые отвечают за блок наставничество и адаптацию новых сотрудников, поступивших на государственную гражданскую службу.

4👍3🤝3

7 Aug 2026, 08:48 UTC309 views9 reactionsread 10 August 2026
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🔤🔤🔤🔤 Как выстроить диалог бизнеса и власти? 🎤 Заместитель директора ВШГУ Президентской академии, кандидат фармацевтических наук Давид Мелик-Гусейнов провёл лекцию о взаимодействии предпринимателей и государства. Он разобрал, что такое GR, зачем нужен и где применяется, — на живых примерах, без академизма и скучных определений, с элементами коммуникации и проектирования. Выступающий также обозначил ключевые сценари

🔥5🗿1🥰1😴1🙊1

6 Aug 2026, 16:32 UTC358 views7 reactionsread 10 August 2026
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🔤🔤🔤🔤🔤 В Воронеже стартовало обучение для руководителей в сфере экономики Сегодня в Воронеже начался третий модуль «Инструменты устойчивого роста инвестиций в регионах России» программы повышения квалификации «Управленческое мастерство руководителя». Она представляет собой управленческий интенсив из четырёх очных модулей, направленный на развитие компетенций лидерства, управления командой, изменениями и конфликтами,

👍4👏21

6 Aug 2026, 11:04 UTC428 views5 reactionsread 10 August 2026
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🌎14 примеров применения ИИ в госуправлении разных стран В аналитическом материале базы знаний Института ВШГУ — обзоре международного опыта применения искусственного интеллекта в государственном управлении. Там и цифры, и сложности, и способы их преодоления. Но главное — живые примеры из разных стран, показывающие, как ИИ реально меняет работу госорганов. Исследование ОЭСР 2025 года, охватившее 200 практик, показал

👏2🔥21

Showing the 12 most recent of 22 posts we hold for @gspmranepa. 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

@gspmranepa 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
12 August 2026
Most recent edit
12 August 2026

Citation-graph rank

Citation-graph rank — 22,953 of 1,350,102entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

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 16 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.

Names

Channels on the register whose handles appear in this channel's posts.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“ВШГУ Президентской академии” (@gspmranepa), 5,841 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/gspmranepa.

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.