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 15 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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 25 days, net +50. 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 2,335–2,402 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
19 Sept 2026, 10:40
2,394
+7
11 Sept 2026, 06:39
2,387
+12
6 Sept 2026, 05:39
2,375
+12
1 Sept 2026, 18:47
2,363
+8
29 Aug 2026, 18:08
2,355
+12
26 Aug 2026, 13:59
2,343
-1
25 Aug 2026, 17:45
2,344
no change
25 Aug 2026, 17:30
2,344
first reading
Engagement
18 posts held, back to 22 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 1 page of Telegram’s post history, 20 posts per page.
ERR · 30 days
25.4%
avg views ÷ 2,394 subscribers
Avg views / post
607
12 posts measured
Reaction rate
1.11%
reactions ÷ views · ER floor
Posts in window
12
of 18 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 25 August 2026
Posts held
18 (22 August 2026 – 25 August 2026)
Views total
7,284
Reactions total
81
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
25 Aug 2026, 17:45 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
9m 23s
Average length
4m 42s
Measured directly from 2 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
157 reactions across 18 posts, in 6 distinct kinds. The most used accounts for 61.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
97
61.8%
🔥
26
16.6%
👍
18
11.5%
🙏
11
7.01%
🥰
4
2.55%
👌
1
0.637%
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 18 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 157 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 22 August 2026 to 25 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.
Going a step further i asked AI specific content and pages from the book which will be useful in these questions. and surprisingly AI has identified more reflections and utility than what had struck me. You are free to try it out as well. If i were an aspirant, either i would have the sense to know myself what to read and what not to read. if not, i will definitely do all these checks before zeroing in on a resource…
In my UPSC experience since 2010 - i have always felt that toppers will be ahead of the curve - in spotting the right & relevant content. And they will be a minority. But then the crowd catches up. But by the time the crowd gets to know it, attempts will almost be exhausted.Similarly there is an inertia as well in letting go of books that have outlasted their utility. I remember when i entered into coaching in 2019, …
"this is the GS 4 ethics question paper. anlayze this questoni paper and understand the nature and demand of the questions asked. Once you are done analyzing i will upload 4 PDFs of different coaching acadamies. I need you to anlayze the content of those PDFs and suggest the best resource that could have helped me tackle the GS 4 questions asked this year. Are you ready ? may i upload the PDfs ?" - this is the prompt…
This is how i asked AI to analyze the utility of these commonly followed books & their relevance for CSE 2026 - GS 4 Ethics. I did ask AI's opinion on the relevance of my book for Ethics as well. And this is the result. I dont know if AI is biased towards my book since the search was conducted on my system. Maybe you may use the same prompts & find it out for yourself on your AI which book if read could have helped …
These are some widely read resources for GS 4 Ethics paper. And why are they widely read ? These books have a reach. But are they really relevant for this years CSE 2026 - GS 4 Ethics paper ? Lets find it out
Qn. Consider a scenario where a mineral-rich State, Odisha, seeks to levy a local infrastructure cess on mineral-bearing lands to fund tribal welfare and environmental rehabilitation in its mining districts. However, the newly enacted central legislation, the MMDR Amendment Act, 2026, prohibits State governments from imposing any tax, cess, or levy on mineral rights or mineral-bearing lands, vesting regulatory contro…
"In the land of the blind, the one eyed is the king" - This is so true about handling the 30% of the challenging qns in every GS Paper in Mains. You do not need to write the perfect answer. An answer that is relevant, convincing, relatable and addresses all parts of the question when qns turn out to be challenging and mind bending is all thats needed. While most aspirants who have submitted their answers could only s…
Qn. Do you agree that the Constitution of India leans towards ‘Federal Supremacy’ in the distribution of powers in the 7th Schedule . How has this leaning strengthened the role of the centre in the working of Indian model of Federalism ? Discuss with contemporary examples (15 marks, 250 words) - no point in writing after referring AI. It will be noticeable.
❤4👍2
Signed Sakthyakrishnan
Showing the 12 most recent of 18 posts we hold for @sakthyakrishnanIAS. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 18 most recent posts we hold, published 22 August 2026 to 25 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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.
Shankar IAS Academy - UPSC @shankariasacademychennai · 60,818 Telegram ranks this channel #2 of 82 here — alongside 81 others — read 6 September 2026
Free UPSC Materials @upscfreematerialsufm · 23,024 Telegram ranks this channel #10 of 71 here — alongside 70 others — read 19 September 2026
The Hindu Newspapers Notes @The_Hindu_NewsPaper_English_PDF · 22,250 Telegram ranks this channel #35 of 66 here — alongside 65 others — read 21 September 2026
UPSC Economy @Upsc_4_economy · 49,623 Telegram ranks this channel #82 of 87 here — alongside 86 others — read 25 August 2026
This channel appears in 4 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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Sakthya Krishnan (IAS 2015,Odisha Cadre, Resigned in 2019)” (@sakthyakrishnanIAS), 2,394 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/sakthyakrishnanIAS.
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.
