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 20 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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 the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (3 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 11 comparable posts for this entry, running 8 November 2024 to 16 March 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 2 channels, the one whose matching posts we hold earliest is @worrld_current_affairs — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_mutual, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
11 measurements spanning 92 days, net -34. 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 792–836 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Nov 2026, 00:56
797
-3
6 Nov 2026, 04:08
800
-1
24 Oct 2026, 08:29
801
-5
11 Oct 2026, 05:22
806
-5
1 Oct 2026, 00:01
811
-6
16 Sept 2026, 21:57
817
-2
9 Sept 2026, 07:37
819
-4
31 Aug 2026, 00:07
823
-4
24 Aug 2026, 04:04
827
-4
15 Aug 2026, 11:54
831
no change
14 Aug 2026, 15:31
831
first reading
Engagement
20 posts held, back to 8 November 2024 — 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 20 posts for this entry, the most recent from 16 March 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
5 reactions across 3 posts, in 2 distinct kinds. The most used accounts for 60.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
3
60.0%
👍
2
40.0%
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 3 of the 20 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 5 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 8 November 2024 to 16 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.
⚠️ FINAL NOTICE: આ ઓફર ફરી નહીં આવે!
👉🏻મિત્રો, GSSSB Field Officer (Class-3) માટેની આ PLATINUM BATCH ની ઓફર આજે રાત્રે પૂરી થાય છે.
👉🏻આવતીકાલથી આ કોર્સ તેની ઓરીજીનલ ફી (₹1199/-) પર જતો રહેશે.
💎 અમે 'સસ્તું' નથી આપતા, 'શ્રેષ્ઠ' આપીએ છીએ:
👉🏻ઘણા વિદ્યાર્થીઓને પ્રશ્ન થાય છે કે આટલા ઓછી પ્રાઈસમાં આટલું કન્ટેન્ટ કેમ?
👉🏻જવાબ છે: અમારો હેતુ દરેક સામાન્ય વિદ્યાર્થી સુધી શ્રેષ્ઠ શિક્ષણ પહોંચાડવાનો છે.
પણ ક્વોલિટી જાળવી રાખવા…
જો તમે Field Officer (Class-3) માટે ગંભીર હોવ તો જ આ વાંચજો...
મિત્રો, માર્કેટમાં 'મોક ટેસ્ટ' ના નામે શું ચાલે છે એ તમે જાણો છો?
❌ જૂના પેપરમાંથી કોપી-પેસ્ટ કરેલા પ્રશ્નો?
❌ ખાલી A/B/C/D જવાબ આપીને પૂરું?
❌ સોશિયોલોજી જેવા વિષયમાં કોઈ સમજૂતી જ નહિ?
📌જો તમે આવી તૈયારી સાથે પરીક્ષા આપવા જવાના હોવ, તો ચેતી જજો! સ્પર્ધા ગળાકાપ છે અને 0.25 માર્ક્સ પણ તમારું સિલેક્શન અટકાવી શકે છે.
🔥 DG Study દ્વારા ગુજરાતની સૌથી પાવરફુ…
📢 GSSSB Field Officer (Class-3) ની તૈયારી કરતા ગંભીર વિદ્યાર્થીઓ માટે ખાસ... 📢
મિત્રો, સ્પર્ધાત્મક પરીક્ષામાં 'સમાજશાસ્ત્ર' (Sociology) એક એવો વિષય છે જે તમને મેરીટમાં સૌથી આગળ લાવી શકે છે, અથવા તમને રેસમાંથી બહાર ફેંકી શકે છે. મોટાભાગના વિદ્યાર્થીઓ સામાન્ય જ્ઞાન (GK) પાછળ દોડે છે, પણ સ્કોરિંગ વિષયોમાં માર્ક્સ ગુમાવે છે.
📄 આજે તમારી સમક્ષ મૂકું છું: 'સમાજશાસ્ત્ર - Subject Wise Paper' આ કોઈ સામાન્ય પ્રશ્નો નથી. આ પે…
‼️સમાજશાસ્ત્ર પેપર 1 Answere Key ‼️
મિત્રો, GSSSB Field Officer ની પરીક્ષા પાસ કરવી હોય તો માત્ર જવાબ ખબર હોવા પૂરતા નથી, તેની પાછળનું લોજિક ખબર હોવી જોઈએ.
📂 આ સાથે આપેલી Answer Key ચેક કરો: આમાં માત્ર 100 પ્રશ્નોના જવાબ નથી, પણ દરેક જવાબની નીચે 'ડિટેલ સમજૂતી' આપી છે. ઓગસ્ટ કોમ્ત હોય કે કાર્લ માર્ક્સ - દરેક કોન્સેપ્ટ ક્લિયર!
જો એક PDF માં આવું ક્વોલિટી કન્ટેન્ટ મળતું હોય, તો આખી બેચમાં કેવું હશે? 🤩
🚀 PLATINUM BAT…
Showing the 12 most recent of 20 posts we hold for @worrld_current_affairs. 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.
મેડિકલ સોશિયલ વર્કર વર્ગ-3 ના aspirent જો પરીક્ષા આપવાના હોય તો આમાં Yes અથવા No કરે
Yes53%
No47%
Shares as published. 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 20 most recent posts we hold, published 8 November 2024 to 16 March 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.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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
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.
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
@worrld_current_affairs 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.
@theonlyiaswe named in 2 posts, 15 August 2026 – 15 August 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.
Niraj Bharwad @nirajbharwad · 114,762 Telegram ranks this channel #23 of 85 here — alongside 84 others — read 14 August 2026
Mechanism Capital @mechcapital · 118,539 Telegram ranks this channel #56 of 92 here — alongside 91 others — read 17 August 2026
This channel appears in 2 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 15 November 2026 — this
entry's latest reading, not the date you are reading this.
“📚𝐂𝐔𝐑𝐑𝐄𝐍𝐓 𝐀𝐅𝐅𝐀𝐈𝐑𝐒📕 જનરલ નોલેજ 📖” (@worrld_current_affairs), 797 subscribers as measured 15 November 2026. Telegram Register, tgregister.com/channel/worrld_current_affairs.
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.
