Ecommerce storefront — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 66% 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 3 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
29 measurements spanning 44 days, net +568. 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 16,876–17,657 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 29
Measured (UTC)
Subscribers
Change
18 Sept 2026, 23:20
17,567
+15
16 Sept 2026, 14:39
17,552
+3
14 Sept 2026, 20:22
17,549
+12
13 Sept 2026, 10:21
17,537
+25
11 Sept 2026, 16:19
17,512
+100
9 Sept 2026, 00:36
17,412
+446
5 Sept 2026, 13:42
16,966
-8
3 Sept 2026, 16:59
16,974
-1
2 Sept 2026, 06:44
16,975
-6
1 Sept 2026, 05:12
16,981
-3
30 Aug 2026, 06:27
16,984
-1
28 Aug 2026, 08:08
16,985
-1
27 Aug 2026, 04:58
16,986
-4
25 Aug 2026, 05:13
16,990
-2
22 Aug 2026, 14:56
16,992
+3
21 Aug 2026, 07:13
16,989
-2
20 Aug 2026, 10:08
16,991
+2
19 Aug 2026, 09:28
16,989
+3
18 Aug 2026, 12:34
16,986
-3
17 Aug 2026, 13:45
16,989
first reading
Engagement
58 posts held, back to 1 August 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 54 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
22.7%
avg views ÷ 17,567 subscribers
Avg views / post
3,980
16 posts measured
Reaction rate
0.425%
reactions ÷ views · ER floor
Posts in window
16
of 58 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 3 September 2026
Posts held
58 (1 August 2026 – 3 September 2026)
Views total
63,690
Reactions total
271
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 09:32 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
1h 35m
Average length
10m 36s
Measured directly from 9 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
1,410 reactions across 55 posts, in 7 distinct kinds. The most used accounts for 63.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👎
891
63.2%
❤
384
27.2%
😁
76
5.39%
👍
41
2.91%
👏
12
0.851%
🔥
4
0.284%
🤩
2
0.142%
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 56 of the 58 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 1,435 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 58 most recent posts we hold, published 1 August 2026 to 3 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.
🎉 *با عضویت در باشگاه پیشکسوتان دیلیمارکت از مزایای دائمی ویژه بازنشستگان کشوری بهرهمند شوید:*
✅️ اعتبار ۶ میلیون تومان
✅ بازپرداخت سهماهه و بدون کارمزد
✅ ۲۰٪ تخفیف محصولات میهن
✅ ۶٪ تخفیف مازاد خرید نقدی
🔻برای کسب اطلاعات بیشتر و عضویت در باشگاه پیشکسوتان دیلیمارکت کافیه روی لینک زیر کلیک کنید:
https://dailymarketstores.com/sc/
🎉 آغاز جشنواره «بازگشت به مدرسه» کفش ملی
🔹این جشنواره با هدف ایجاد پویایی در شبکه فروش، پاسخگویی به نیاز خانوادهها در آستانه آغاز سال تحصیلی جدید و فراهمسازی شرایط مناسب برای دسترسی دانشآموزان به کفشهایی راحت، باکیفیت و متناسب با فعالیتهای روزانه آنان طراحی و اجرا شده است.
🔸سید محمد جعفری و رئیس هیئتمدیره و مدیران کفش ملی با امضای پوستر یادبود جشنواره «بازگشت به مدرسه»، بر عزم مشترک مجموعه برای تحقق برنامهه…
⚡همزمان با هفته دولت انجام شد؛
طرح مطالبات و دغدغههای بازنشستگان اصفهان در دیدار با معاون توسعه مدیریت و منابع صندوق
🔹حشمتالله سلیمانی، معاون توسعه مدیریت و منابع صندوق بازنشستگی کشوری، همزمان با دومین روز هفته دولت و در پی درخواست کانونهای بازنشستگی استان اصفهان، با حضور در «خانه امید» این استان، در دیداری با رؤسای کانونهای بازنشستگی، بهصورت مستقیم در جریان مهمترین مطالبات و دغدغههای بازنشستگان قرار گرفت و …
⚡ تمدید مهلت ثبت درخواست انصراف و برقراری بیمه تکمیلی درمان تا ۱۲ شهریور
🔹 به منظور تداوم نظم اجرایی و حسن انجام امور و با هدف تسهیل فرآیندهای اجرایی، مهلت ثبت درخواستهای مرتبط با بیمه تکمیلی درمان دی برای بازنشستگان، از کارافتادگان و وظیفه بگیران تمدید شد.
🔸 دسترسی به سامانۀ ثبت درخواستهای بیمهای در وبسایت رسمی صندوق، تا پایان روز ۱۲ شهریورماه ۱۴۰۵ (در چارچوب سقف سهماه ابتدای قرارداد) برای عموم متقاضیان فعال…
شریفنوا؛ تجربهای برای ساختن آینده 🌱
پیرو تفاهمنامه دانشگاه صنعتی شریف و صندوق بازنشستگی کشوری و با هدف ایجاد فرصتهای تازه برای یادگیری، توانمندسازی و بهرهگیری از سرمایه ارزشمند تجربه بازنشستگان، «شریفنوا» طراحی شده است.
بازنشستگی پایان مسیر نیست؛
فرصتی است برای اینکه آنچه در سالها آموختهاید، با دانش و فرصتهای امروز پیوند بخورد.
در شریفنوا، قرار است تجربهها دوباره به جریان بیفتند؛
با یادگیری مهارتهای کا…
#معرفی_کتاب_بازنشستگان
#کتاب_باز
*سازمان های نارس- نظریه نوین برای تشخیص نارسی*
پدید آور: *دکتر فرخ قربانی نامور*(1351-آذربایجان شرقی)
بازنشسته دانشگاه فرهنگیان
استاد و صاحبنظر و اندیشمند حوزه منابع انسانی
عضو هیات علمی دانشگاه فرهنگیان
📕قطع کتاب: وزیری
تعداد صفحات: 251 صفحه
شابک: 9786004835879
ناشر: پژوهشهای دانشگاه
زبان کتاب: فارسی
نوبت و سال چاپ: چهارم-1405
🔹 کتاب «سازمانهای نارس؛ نظریه نوین در تشخیص نارسی س…
⚡همزمان با هفته دولت و در جریان سفر استانی به کهگیلویه و بویراحمد انجام شد؛
از پیگیری مطالبات بازنشستگان تا بررسی طرحهای توسعهای بنگاههای صندوق در سفر دکتر ازوجی به یاسوج
🔹دکتر علاءالدین ازوجی، مدیرعامل صندوق بازنشستگی کشوری و نماینده دولت در سفر به استان کهگیلویه و بویراحمد، ضمن دیدار و گفتوگو با نمایندگان کانونهای بازنشستگان و بررسی مهمترین مطالبات آنان، از طرحها و مجموعههای اقتصادی تحت پوشش صندوق در یاسو…
⚡در جریان سفر استانی نماینده دولت به فارس در هفته دولت انجام شد؛
بازدید دکتر ازوجی از بنگاههای اقتصادی صندوق بازنشستگی در استان فارس با محوریت تولید، سرمایهگذاری و صیانت از دارایی بازنشستگان
🔹مدیرعامل صندوق بازنشستگی کشوری و نماینده دولت در سفر به استان فارس، از مجموعههای اقتصادی و گردشگری تحت پوشش صندوق بازدید کرد و ضمن بررسی طرحهای توسعهای و تولیدی، بر تأمین منابع مالی، بازگشت بنگاهها به ظرفیت مطلوب تولید، …
دکتر ایرج نبیپور؛ پزشک، پژوهشگر و استاد بازنشسته دانشگاه:
باید سالها پیش از سالمند شدن، برای سالمندی سالم برنامهریزی کنیم
🔹دکتر ایرج نبیپور، پزشک، پژوهشگر و استاد دانشگاه علوم پزشکی بوشهر، در گفتوگو با یک نشریه محلی از مسیر چند دهه فعالیت علمی خود میگوید؛ مسیری که از پزشکی و پژوهش آغاز شده و به مطالعه سالمندی، توسعه زیرساختهای علمی جنوب، تاریخ پزشکی و خلیجفارس امتداد یافته است.
🔸او با تأکید بر ضرورت برنامه…
⚡مدیرکل حقوقی و امور قراردادهای صندوق بازنشستگی کشوری تأکید کرد:
آگاهی شاغلان از مقررات بازنشستگی، راهکار پیشگیری از دعاوی و اطاله دادرسی/بخش قابل توجهی از اختلافات حقوق بازنشستگی، ریشه در احکام دوران اشتغال دارد
🔹هرگونه تصمیم دستگاه اجرایی درباره سوابق خدمتی، مزایا، فوقالعادهها، رتبه و گروه شغلی که در محاسبه حقوق بازنشستگی مؤثر است، باید با در نظر گرفتن مقررات مورد عمل صندوق بازنشستگی کشوری انجام شود تا از شکلگ…
#اینفوگرافی
ثبت نام اینترنتی وام ازدواج فرزندان بازنشستگان کشوری
🟢 ثبتنام اینترنتی وام ازدواج فرزندان بازنشستگان و وظیفهبگیران صندوق بازنشستگی کشوری از ۳ شهریورماه ۱۴۰۵ آغاز شده و تا اول مهرماه ۱۴۰۵ ادامه دارد.
💰 مبلغ تسهیلات: ۸۰ میلیون تومان
💳 بازپرداخت: ۳۶ ماهه
📌 کارمزد: ۵ درصد
💍 تاریخ عقد: از اول مهر ۱۴۰۳ تا پایان مهلت ثبتنام
📄 ارسال مدارک: نیاز نیست؛ اطلاعات از طریق سامانه ثبت احوال راستیآزمایی میشود.
⚠️…
👎13❤3
Showing the 12 most recent of 58 posts we hold for @bazneshaste_news. 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 2 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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@bazneshaste_news named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@sharifstaradmin named in 6 posts, 18 August 2026 – 4 September 2026
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.
آذرالسلطنه @mahisefatazar · 22,471 Telegram ranks this channel #27 of 64 here — alongside 63 others — read 20 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“صندوق بازنشستگی کشوری” (@bazneshaste_news), 17,567 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/bazneshaste_news.
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.