e-ISSN 2785-5953
Bhasha
Vol. 1 – Issue 1 – April 2022
‘Sanskrit‑Speaking’ Villages,
Faith‑Based Development
and the Indian Census
Patrick S.D. McCartney
Nanzan University Anthropological Institute, Nagoya
Abstract Over three sections, the 2001 and 2011 Indian censuses are scrutinised to
locate, down to the sub‑district administrative and village levels, where L1‑L3 (first to
third language) Sanskrit tokens were returned during census enumeration. First, there is
a theo‑political discussion of Sanskrit’s imaginative power for faith‑based development.
This includes a discussion on how ‘Sanskrit‑speaking’ villages signify an ambition toward
cultural renaissance. Next, Sanskrit’s national‑level enumeration is discussed. Finally,
closer scrutiny is paid to the top four states (Maharashtra, Bihar, Madhya Pradesh, and
Uttar Pradesh). On average, more Sanskrit tokens were returned by men than women;
92% of L2‑Sanskrit tokens are linked to L1‑Hindi; most L1‑L3‑Sanskrit tokens cluster
with Hindi, English, and/or the State Official Language; most Sanskrit tokens are Urban,
as opposed to Rural; and most tokens are found across the Hindi Belt of north India.
Keywords ‘Sanskrit‑Speaking’ villages. Hindu nationalism. Linguistic utopia. Social
imaginary. Mother tongue.
Summary 1 Introduction. – 2 Sanskrit, Theo‑Politics, and Faith‑Based Development. –
3 Comparing 2001 and 2011 Census Results. – 4 An Explication of Census Data in Several
States. – 4.1 Maharashtra. – 4.2 Bihar. – 4.3 Madhya Pradesh. – 4.4 Uttar Pradesh. –
5 Concluding Remarks.
Peer review
Submitted 2021-12-10
Edizioni Accepted 2022-03-02
Ca’Foscari
Published 2022-04-29
Open access
© 2022 | bc Creative Commons Attribution 4.0 International Public License
Citation McCartney, P.S.D. (2022). “‘Sanskrit-Speaking’ Villages, Faith-Based
Development and the Indian Census”. Bhasha, 1(1), 77-110.
DOI 10.30687/bhasha/2785-5953/2022/01/007 77
Patrick S.D. McCartney
‘Sanskrit-Speaking’ Villages, Faith-Based Development and the Indian Census
1 Introduction
bhāṣā saṃskṛtāpabhraṃśaḥ bhāṣāpabhraṃśastu vibhāṣā |
sātattaddeśa eva gahvaravāsināṃca prakṛtavāsināṃca ||
Abhinavabharati 17.49
The corruption of Sanskrit is bhāṣā, and the corruption of bhāṣā is vibhāṣā.
It is the language of the same countries of forest dwellers and of rustic people.
(Kavi 1934, 376)
This paper is part of the Imagining Sanskritland project, which fo‑
cuses on locating and documenting how, where, and why the Middle
Indo‑Aryan language, Sanskrit, is spoken in the twenty‑first centu‑
ry. This builds on the previous work of Nakamura (1973), Hock and
Pandaripande (1976), Hock (1991), Aralikatti (1989; 1991), Aklujkar
(1996), Hastings (2004; 2008), and Deshpande (2011; unpublished).
Generally, this project expands beyond linguistic analysis of sen‑
tence structure to document the aspirations, ideologies, and moral
horizons inherent in identifying as a speaker, as well as document‑
ing second‑language acquisition through a focus on imperfect learn‑
ing, substrate interference, and bilingualism.
The project first focused on code‑switching between Hindi and
Sanskrit and the transubstantiation of symbolic capital in a resi‑
dential Sanskrit college/yoga ashram in Gujarat, India (McCartney
2011; 2014a; 2017a; 2018a). Another focus was the two‑week intensive
speaking course in New Delhi (McCartney 2014b). The focus pivoted
to include a relatively famous ‘Sanskrit‑speaking’ village in Madhya
Pradesh, India (McCartney 2015; 2016a; 2016b; 2016c; 2017b; 2017c;
2017d; 2018b), which includes discussion of language revival and hy‑
bridisation (McCartney, Zuckermann 2019). This combines with ana‑
lysing the theo‑politics of Sanskrit’s imaginative consumption within
the transglobal wellness industry and the topic of ‘yoga fundamental‑
ism’, which maps out the distanced and banal ways that consumption
of yoga lifestyles can potentiate tacit and unwitting support of Hindu
supremacism (McCartney 2017e; 2017f; 2017g; 2019a; 2019b; 2020).
More recently, the project has pivoted to cover matters related to
Sanskrit’s soft power potential within the context of faith‑based, sus‑
tainable development and competitive diplomacy. This involves envi‑
ronmental impact assessments of yoga lifestyle brands and the culti‑
vation of nostalgic moods predicated by Neo‑Romanticism, mystical
holism, and dark green religion (McCartney 2021a; 2021b; 2021c).
Informed by Deumert’s (2009) and Posel and Zeller’s (2015) de‑
mographic analyses of census data related to language shift and bi‑
lingualism in South Africa, this project pivots to look for Sanskrit
I would like to thank Andrey Klebanov for helping with particular issues in develop‑
ing this paper.
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(‘speakers’) in the Indian census data. An initial result, upon which
this present paper directly builds, is McCartney (unpublished). The
policy of India’s census enumeration states that if the number of
speakers of any language drops below 10,000 then it will no long‑
er be reported as a separate language (Goswami 2012).1 If Sanskrit
were to dip below the threshold, this would have unintended con‑
sequences for its soft power deployment. Therefore, the politics of
census enumeration for the purposes of state building are relevant.
Simply looking for Sanskrit speakers is something of a fool’s errand.
Sanskrit is a post‑vernacular language in a perpetual state of acqui‑
sition. The media only reports the perceived success of Sanskrit’s re‑
vival (Indian Yug 2020).
In short, India’s 2011 census results clearly demonstrate that San‑
skrit ‘speakers’ are overwhelmingly found in urban areas spread
across the ‘Hindi heartland’,2 which is only a part of India’s complex
linguistic ecology and “linguistic area” (Emeneau 1956). What this
paper does is use the Indian government’s census data to geograph‑
ically locate where people who identify as speakers of Sanskrit were
at the time of census enumeration. For now, this is as good as it gets,
as the data presented below are not capable of verifying the fluen‑
cy of people who claim to speak Sanskrit. Discussion of several is‑
sues relating to this are found across the project’s publications men‑
tioned above. The outcomes from this present paper include future
research being more strategic.
Even though some consider Sanskrit to be the “language of the ru‑
ral masses” (Deopujari 2009) and the “language of future India” (Mo‑
han 2020), it is also thought that “Sanskrit is the forgotten language
of urban India” (Indian Eagle 2020) and that “NASA believes San‑
1 This is one reason why the RSS (Rashṭriya Svayamsevak Sangh, ‘National Volun‑
teer Corps’) “wants citizens to voluntarily register Sanskrit as their second language
in the census. The RSS feels that if people register the language, the final census da‑
ta would reflect higher literacy of Sanskrit, which will force the government to take
measures to preserve the language” (Tare 2010).
2 Compare the notion of the “Vedic God” by Hebden (2011). The geographic focus of
this paper is the ‘Hindi Heartland’ or ‘Hindi Belt’, which covers most of the plains of
north India, where Sanskrit’s close relatives – Hindi and its related languages – are spo‑
ken. This is pertinent because, as is discussed below, this is the linguistic area where
the census results indicate most of the ‘Sanskrit speakers’ live. As is evident, below,
the link between people who identify as Sanskrit speakers with both Hindi and Eng‑
lish is immense. By way of example, the state of Bihar’s Sanskrit areas is discussed be‑
low. This paper expands upon Jha’s (2017) explanation of how studies of language poli‑
tics in north India tend to focus on the Hindi‑Urdu debate. This debate builds on a cen‑
turies‑old development of language order in premodern India (Ollet 2017), taking on
communalist narratives. This culminated in the nineteenth century around which of
these mutually intelligible languages – Hindu and Urdu, which derive from Hindustani,
but use different scripts, respectively, Devanāgarī दे व नागरी and Nastaʾlīq – نستعلیقshould
become the national language. Currently, India does not have a national language. In‑
stead, it has two official languages, Hindi and English (Dasgupta 1995).
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skrit is a scientific language for programming” (TNN 2019). More‑
over, Sanskrit is thought to be a “gift of India for [the] entire hu‑
manity” (India Education Diary Bureau 2020) and that the “Sanskrit
effect” is caused by “chanting Sanskrit”, which “increases brain cog‑
nitive areas” (Sanskriti 2018). The benefits of chanting are predicted
to extend beyond humans, as “Cows will talk in Tamil and Sanskrit”
(Patherpanchali 2018). Back down on the ground, it is difficult to lo‑
cate Sanskrit speakers because the available information are unre‑
liable factoids mentioned on the internet,3 copied and pasted from
3 Yet, these lofty ambitions have humble origins amongst the mythical villages, whose
inhabitants are meant to be grateful that Sanskrit’s perceived civilising power will fi‑
nally reach them, even if this ideological benevolence is soaked in a neo‑colonial San‑
skritisation impetus that is made explicit in ways, such as “Saṃskṛtaṃ sarveṣāṃ kṛte…
sarvadā; Sanskrit for everyone… forever” (Amaravāṇi 2020). Strength, it seems, is not
found in linguistic diversity. Amara‑vāṇī (immortal‑language) is ultimately a part of
Samskrita Bharati, which itself is the linguistic node of the more prominent Hindu na‑
tionalist parent organisation, the Rashṭriya Svayamsevak Sangh (RSS). It is through
its international branch, the Hindu Svayamsevak Sangh (HSS), that Samskrita Bharati
operates at an international level. It mostly services the Indian diaspora through cul‑
tural and linguistic events, which can be an opportunity for the collapsing of the ‘big’
versus ‘little’ tradition binary (Vertovec 1994), such as a potential muddling of San‑
skrit as it goes through its interlanguage stage of acquisition. However, the expan‑
sion beyond the imagined borders, especially through extending into cyberspace, re‑
quires a recalibration of relations, especially to the puṇya bhūmī (‘sacred land’) of the
Hindutvavādins imagination, within the context of transnational development and mul‑
tiple modernities (Jaffrelot 2017). After all, “Sanskrit is a gift of India for entire hu‑
manity”. At least, that is what India’s HRD Minister, Ramesh Pokhriyal, asserted just
after the Central Sanskrit Universities Bill, 2020 was passed by India’s upper house
of parliament to upgrade three Deemed Sanskrit Universities to Central University
status (India Education Diary Bureau 2020). Amaravāṇī promotes Sanskrit through
songs. One example is the song Viśva‑bhāṣā Saṃskṛtam (‘The Universal‑Language is
Sanskrit’). Information on the song’s page, on Amaravāṇī’s website, also claims, that
“There are many villages in India where the entire population speaks solely and fluent‑
ly in Saṃskṛtam!” (Amaravāṇi 2020). Such truth claims are a curious thing. I am re‑
minded of one verse from a seventh century Ayurvedic text, which discusses poor vi‑
sion resulting from false perception: “Dūrāntikasthaṃ rūpañca viparyāsena manyate |
doṣe maṇḍalasaṃsthāne maṇḍalānīva paśyati || AS.Utt.15.4 ||” “Due to false perception
(viparyāsa), a patient perceives a thing located far away, as close by, and things located
close by, as far away” (Aṣṭhāṅgasaṅgraha, Uttarasthānam, 15.4 [Vāgbhaṭa 2020]). In a
topsy‑turvy way, viparyāsa refers to the act of imagining something to be real and true,
when it is false. The term niścaya can mean both correct perception and enquiry. We
find in the Vaiśṇava tradition encouragement to cultivate niścaya (Śrīmad Bhāgavatam
3.26.30), which is recommended for both soteriological aspirations and mundane mat‑
ters. This concept is similar to that of Nāgārjuna (c. 150 CE-c. 250 CE), who discussed,
in the Mahāprajñāpāramitāśāstra, the concept of pratītyasamutpāda. This refers to the
“basic principle of thought that no two contradictory judgements can hold good in re‑
gard to the same thing in the same respect” (Ramanan 1987, 167). In other words, ‘San‑
skrit‑speaking’ villages either are true and do exist or they do not. There is very lit‑
tle available evidence, be it documentary, direct, real, circumstantial or testimonial.
Furthermore, what percentage of a village’s population and to what degree of fluency
and ordinal ranking of usage, considering frequency of code‑switching, domains and
topics, might be the minimum requirements to satisfy claims of any village being one
that is ‘Sanskrit‑speaking’?
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other websites lacking accurate details. Nonetheless, these factoids
are enough for people to believe that ‘Sanskrit‑speaking’ villages
exist.4 People rely on this meme to provide emotional reinforcement
for deeply held religious beliefs hoping it will re‑enchant the world
to provide profound meaning in one’s life. ‘Sanskrit‑speaking’ villag‑
es endow the world with a perceived sense of divinity, meaning, and
significance. As an empty signifier, the village is remote enough to
remain perceived as an infallible closed circuit. Similarly, Olshan‑
sky, Peaslee and Landrum (2020) provide insight into the cognitive
defence mechanisms of flat earthers, which include motivated rea‑
soning to dilute cognitive dissonance and maintain cognitive consist‑
ency. Having visited several of these so‑called ‘Sanskrit‑speaking’
villages, I became increasingly frustrated, as most of these villages
contain hardly anyone who can hold a casual conversation across gen‑
eral domains and topics or utter increasingly complex sentence pat‑
terns, and include more complicated use of tense, aspect, or mood.
Nonetheless, throughout the last decade, my primary question has
been: “Where are the Sanskrit speakers?”.5
Jhirī is a village in Madhya Pradesh that I have paid more atten‑
tion to (McCartney 2015; 2016a; 2016b; 2016c; 2017b; 2017c; 2017d;
2018b) where apparently everyone speaks Sanskrit (Samskrit101
2009). Oblivious to issues of linguistic human rights (Skutnabb‑kan‑
gas 2012), Ghosh (2008) celebrates how the residents “hardly speak
the local dialect, Malvi, any longer. Ten years have been enough for
the sanskritization of life here”. A potent claim that “even those who
don’t know the technicalities of the language still speak fluent San‑
skrit” (Hindutvainus 2011) is demonstrably false. For instance, while
conducting fieldwork in Jhiri, one of the residents repeatedly claimed
that everyone in village fluently spoke Sanskrit. Beaming with pride,
he often emphatically asserted, “Bhoḥ, asmin grāme iva sarve janāḥ
saṃskṛtaṃ vadituṃ śakyante khalu [Sir, in this village everyone can
speak Sanskrit!]”. However, this was easily disproven by speaking to
4 My term, laukika‑saṃskṛta‑bhāṣā‑aviparyāsa‑ābhāsa‑samanveṣaṇam, refers to the at‑
tempt to look everywhere (samanveṣaṇa) for the semblance (ābhāsa) and distorted per‑
ception (aviparyāsa) of vernacular (laukika) variants, or regional dialects, of Sanskrit
(saṃskṛta), as a spoken language. This includes its mention in yoga‑related outlets (Di‑
zon 2016; Bedewi 2020). By first identifying the ‘pseudo‑perception’ (pratyakṣa‑ābhāsa)
found in discourse (vyavahāra), the process moves to falsifying (dūṣayati) fallacies
(hetvābhāṣa) related to the enduring claims about ‘Sanskrit‑speaking’ villages, which
are legion.
5 In logic, ābhāsa takes the meaning of ‘erroneous though plausible argument’. These
rumours act as a buffer warding off existential anxiety. At least it is potentially com‑
forting to know that a ‘real’ and ‘true’ India still exists and that “India’s own Jurassic
Park” is found in rural Madhya Pradesh, in a village that “is a lost world that has been
recreated carefully and painstakingly, but lives a precarious existence, cut off from the
compelling realities of the world outside” (Ghosh 2008). The village holds an ambigu‑
ously utopian relation to future India (Nandy 2001; Mohan 2012).
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anyone within arm’s reach, who would require prompts from others
as they could not reply to simple sentences, such as “Bhavataḥ nāma
kiṃ [What is your name?]” or “Mitram, kutra gacchasi [Friend, where
do you go?]”, let alone pass sentence repetition tests. Yet, these ru‑
mours become factoids and bloom into unassailable facts in support
of “core Indian values” (Prabhu 2014). One potent example is the use
of spoken Sanskrit to sell a motorbike, which uses a ‘Sanskrit‑speak‑
ing’ village as the backdrop (Sharma 2009).
One issue with validating the returned Sanskrit tokens in the cen‑
sus data is that they are self‑reported. Another issue is that census
enumerators are bound by law not to question the maximum three
languages given. Therefore, if someone believes they speak Sanskrit
(or any other language) and identify as a speaker of Sanskrit then
it becomes a demographic fact.6 Simply put, one token refers to one
individual instance of someone claiming to be either a L1 (‘moth‑
er tongue’), L2 (second‑language), or L3 (third language) speaker.7
These epistemic methodological issues have been discussed at eve‑
ry census (Office of the Registrar General 2020).
All of the data are publicly available in downloadable spreadsheets
(Office of the Registrar General 2020). The 2011 data come from the
relevant C‑16 (‘mother tongue’)8 and C‑17 (bi‑/tri‑lingualism) tables,
which only became available in late 2018. Multiple versions of these
6 India, like many nations, has used different and equally ambiguous terminology to
capture the primary language(s) used by their citizens. There are actually three lan‑
guage ‘situations’ that can be captured by censuses: (a) the language first used by the
respondent; (b) the language most commonly used by the respondent at the time of the
census; and (c) the knowledge of particular official language(s) by the respondent (Arel
2004). The Indian census does not appear to achieve this tertiary system, simply be‑
cause it does not ask the necessary questions. Is this due to either pragmatic expedien‑
cy, ideology, or both? Building upon Foucault 2007, Duchêne, Humbert, Coray 2018 ex‑
plain the consequences of reducing real world complexities through statistics to quan‑
tifiable categories. These can become tools of governance for national solutions. This,
after all, is probably the point. Yet, if there is an ideological component, it then becomes
more challenging, particularly when added to the epistemic relativism of self‑report‑
ing, to gather meaningful data to implement productive policy.
7 This present study does not have the capacity to verify whether these tokens trans‑
late into real‑world pragmatic abilities to communicate in Sanskrit.
8 A ‘mother tongue’, is defined in the Indian Census guidelines (3.1) as, a “the lan‑
guage spoken in childhood by the person’s mother to the person. If the mother died in
infancy, the language mainly spoken in the person’s home in childhood will be the moth‑
er tongue. In the case of infants and deaf mutes, the language usually spoken by the
mother should be recorded. In case of doubt, the language mainly spoken in the house‑
hold may be recorded” (Office of the Registrar General 2020). Section 3.2.a‑d stipu‑
lates that an ‘enumerator’ is “Bound to record the language as returned by the person
as her/his mother tongue”; and that they must record the “mother tongue in full, what‑
ever is the name of the language returned by the respondent and do not use abbre‑
viations”. Collectors are not expected to determine if a “language returned by a per‑
son is a dialect of another language”; and, if there is any “relationship between moth‑
er tongue and religion” (Office of the Registrar General 2020). This gets complicated
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tables exist, as each state has a separate C‑16/‑17 table. Having col‑
lected and sorted millions of data points, each table was filtered us‑
ing excel data analytic functions. The subsequent aggregate token
amounts were then cross‑analysed over several levels of administra‑
tion. These levels include the national, state, district, sub‑district lev‑
els, as well as rural and urban zones and sex ratios.
A key finding demonstrates high levels of affinity between the tri‑
une of Sanskrit (S), Hindi (H), and English (E), which is also nuanced
by each state’s official language (SOL). This means that people who
identify as L1‑L3 speakers of Sanskrit are overwhelmingly clustered
within a specific set of L1‑L3 languages, which more often than not
includes Hindi and English.9 Therefore, the statistically relevant iden‑
tity of the typical ‘Sanskrit speaker’ is an educated, middle‑class ur‑
banite who lives in north India.10
Based on 2011’s C‑16 table, the total nation‑wide number of L1‑San‑
skrit Persons amounts to 24,821 (tokens); [fig. 1] shows the totals for
all states and union territories.
when Hindu nationalist groups urge people to list Sanskrit as their L1 in the lead up
to each census (Tare 2010).
9 This has much to do with India’s language planning policy, which prefers a Sanskri‑
tised Hindi as the official language (see Articles 343 and 351 of India’s constitution).
For example, L1‑S_L2‑H_L3‑E would mean an individual’s languages are L1‑Sanskrit,
L2‑Hindi, and L3‑English. The following formula S=(L1α_L2β_L3γ)(SOL) is an attempt
to articulate the ways in which Sanskrit can be found within complex linguistic ecolo‑
gies and the influence of the state language in modifying the triadic SHE. For instance,
across the language area of Maharashtra, the state language, Marathi, competes, as
it were, for space on, like different taste buds, on the tongues of the state’s citizens.
10 In the post‑Independence era, studies related to contemporaneous spoken San‑
skrit were initiated first by the Sanskrit Commission (Azad 1957), which laid down sev‑
eral recommendations for preserving and promoting Sanskrit as a spoken language,
some of which have been successfully introduced. Deshpande (2011) explains how, due
to the changes in the three‑language educational policy, Sanskrit has fared better in
the Hindi speaking states than in the non‑Hindi speaking states, where a dramatic re‑
duction in students studying Sanskrit occurred once it became optional in 1968 (see
Azad 1957, 99). This does not stop activists from trying to install Sanskrit as the nation‑
al language (rāṣṭra‑bhāṣā) and global lingua franca (viśva‑bhāṣā) (Ramaswamy 1999).
As well, these language politics have long encoded Hindi as a hegemonic language yet
raise the status of Sanskrit. Complementing this, Babu (2017, 113) explains that in In‑
dia Sanskrit sits atop the linguistic hierarchy and caste system by invoking the notion
of catur‑varṇa (‘four‑classes’) by positing Sanskrit as occupying a privileged position
and English (which is a rank outsider in the constitutional scheme), as a language with
emancipatory capacity due to its positioning outside the legitimised hierarchy.
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Figure 1 2011 India: States L1‑Sanskrit. (India 2020)
A deeper historical review of Sanskrit’s enumeration across all 15
censuses occurs in [tab. 1], which provides a cursory glance at San‑
skrit’s India‑wide total Persons’ results from 1881 to 2011.
Table 1 Total Persons L1‑Sanskrit returns, 1881‑201111
Year Total Sanskrit Total population %
1881 1,308 224,000,000 0.0006
1891 308 287,000,000 0.0001
11 The Sanskrit data at each census is located in Plowden 1883, 132; Baines 1893,
144; Risley, Gait 1903, 164, 174; Gait 1913, 106; Marten 1923, 96; Hutton 1933, 492;
Yeats 1943, 9; Mitra 1994; Office of the Registrar General 1954, 7; Mallikarjun 2002;
Breton 1976, 304; Office of the Registrar General 2020. Yeats explains that “The lan‑
guage and script questions have not been tabulated and I make now a recommendation
to the Government of India that they be not tabulated even if the suspended operations
are resumed” (1943, 9). Mitra (1994, 3207) explains that war, communal tensions, and
Yeat’s transition to self‑enumeration from household enumeration resulted in a com‑
pletely botched census that produced incoherent results left unpublished. Mallikarjun
(2002) shows that of the 2,554, one person identifies as a speaker of ‘Vedic’ Sanskrit
and another as a speaker of VedPali, while 93 and 5 people respectively claim to speak
Pali and Prakrit. Breton (1976, 304‑8) provides a good overview of the 1961 census.
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Year Total Sanskrit Total population %
1901 716 238,396,327 0.0003
1911 360 252,093,390 0.0001
1921 356 251,321,213 0.0001
1931 1,181 278,977,238 0.0004
1941 N/A 318,660, 580 N/A
1951 555 361,088,090 0.0001
1961 2,554 439,234,771 0.0006
1971 2,212 548,159,652 0.0004
1981 6,106 683,329,097 0.0009
1991 49,736 846,427,039 0.006
2001 14,135 1,028,737,436 0.001
2011 24,821 1,210,854,977 0.002
This paper has three main sections. The first (§ 2) discusses key
theo‑political points related to Sanskrit’s imaginative power. § 3 ex‑
plicates Sanskrit’s national‑level enumeration comparing the 2011
and 2001 censuses. § 4 burrows down to the lowest administrative
levels of four states to show which districts, sub‑districts (tehsil/ta‑
luk, or taluq), and in some cases, blocks, returned the highest num‑
bers of L1‑L3 Sanskrit tokens.
2 Sanskrit, Theo‑Politics, and Faith‑Based Development
Inspection of faith‑based competitive diplomacy, in relation to Yoga
and Sanskrit, is sparse.12 The ways in which Sanskrit is imbricated
is often under appreciated. While for some, Sanskrit might be a dead
language and a symbol for millennia of oppression, for others it is a
treasure trove of untapped knowledge that might just save humanity
and a heritage language one might like to speak (McCartney 2021a).
Sanskrit helps define and chart one’s path toward a moral horizon.
This speaks more about temporalities of becoming rather than be‑
ing (Fahy 2020). It helps an individual link to an archaic modernity
or futured‑past and potentially return to an imagined Vedic ‘Golden
Age’ fuelled by re‑enchanting, eco‑sustainable, neo‑Romantic, mys‑
tical holism (Hebden 2011; Subramaniam 2019). However, Sanskrit’s
reclamation and acquisition are indelibly constrained by substrate
12 The most closely related is Jacobs’ documentation (2016) of the world’s largest vol‑
unteer‑based charity, the Art of Living Foundation, that originates from India. Watanabe
(2019) explores a Japanese organisation’s operations in south‑east Asia. Haynes’s (2021)
edited volume explores international relations across several religions. Nelson (2021),
however, provides the most comprehensive account of faith‑based NGOs as non‑state
political and moral actors.
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interference from the L1s influencing how it, as a L2, is spoken. One
of the key assets used to justify Sanskrit’s role as a tool for develop‑
ment is its perceived linguistic purity. It is argued that only a ‘pure’
Sanskrit can deliver the utopian world it inspires. What, exactly,
might a pure Sanskrit sound like and how might it power anything?
Answering this question is a particularly vexing matter, especially
when considering that the earliest layers of the Vedic corpus contain
hundreds of loan words from other Indo‑European and non‑Indo‑Eu‑
ropean languages.13 During the post‑Vedic Period (c. 500 BCE), ver‑
nacular Sanskrit, otherwise known as bhāṣā, was referred to as the
language of the conquerors (Burrow 1965). Burrow showed through
a study of the morphology of Classical Sanskrit how the diversity of
forms prevalent in the earlier Vedic language reduced significant‑
ly, even though it did become the language of Vedic and later Hin‑
du texts, commentaries, rituals, and literature (Subbarao 2008). In
the contemporary revival movement, this simplification has contin‑
ued to the point where vernacular Sanskrit can be feasibly equated
with a Sanskritised form of Hindi (Deshpande 2011; unpublished).
The production, reception, and consumption of the ‘Sanskrit‑speak‑
ing’ village narratives across various media appear to function in a
similar way to phalaśruti paratexts. The phalaśruti is the textual com‑
ponent listing the benefits of hearing or reciting the particular text.
Taylor (2012, 94‑5) explains that these “fruits of hearing” texts of‑
ten include potential punishments and dangers listed along with the
promise of heavenly rewards and that this “is a way of enabling the
discourse to function as ‘true’ and is at least partly driven by a dis‑
tinctly earthly agenda”. Another similarity between Taylor’s discus‑
sion of paratexts and the ‘Sanskrit‑speaking’ village discourse is the
way in which quantifiable and qualifiable measurements seem illu‑
sive. Nonetheless, the ‘Sanskrit‑speaking’ village boots this signal.
Consider the example of this faith‑based development narrative that
has evolved over the past decade in the state of Uttarakhand, which,
in 2010, voted in Sanskrit as its second official language (Trivedi
2010; McCartney 2021c). Even though this project was implemented a
decade ago, and has endured changing governments and allegations
of corruption, by 2013 ₹21 crore (USD 275 million) had already been
spent on promoting Sanskrit education in Uttarakhand. Regrettably,
there is very little to show for it (Singh 2015). Recently, however, an
updated policy has increased this imposition of language shift toward
the target language, Sanskrit (Ahmad 2020). This new policy aims to
13 Historical linguistics demonstrates that the oldest intangible artefact of the San‑
skrit canon, the Ṛgveda (c. 1600‑1100 BCE), contains approximately two percent non‑Ar‑
yan vocabulary, idiomatic expressions and phonemic influences, which are derived from
the Dravidian language family, the Bactria‑Margiana Archaeological Complex, and the
Harappan Kubhā‑Vipāś Substrate (see Witzel 2010).
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create a Sanskrit village in every ‘block’ (an administrative division
often confused with sub‑districts) of Uttarakhand (News Desk 2020;
Upadhyay 2020). The state of Uttarakhand consists of two Divisions,
13 Districts, 79 Sub‑districts, and 97 Blocks. One wonders how much
more investment might be needed to transform 97 villages scattered
across the Himalayas into saṃskṛta‑grāmāḥ (‘Sanskrit‑villages’). Af‑
ter all this investment not one L1‑Sanskrit token comes from any vil‑
lage or rural area.14 While 70% of the state’s total population live in
rural areas, 100% of the state’s total (n=246) L1‑Sanskrit tokens are
linked to urban areas.
The ideology behind this top‑down development project aims to
reverse engineer India and the world through implementing a ‘dhar‑
mic’ lifestyle predicated by Sanskrit and Yoga. It aims to reform so‑
ciety toward an imagined Sanskritland, where just like the follow‑
ing song that attendees at Samskrita Bharati language camps learn,
the aspiration is that Sanskrit will be spoken “gṛhe gṛhe [in eve‑
ry home], grāme grāme [in every village], nagare nagare [in every
city], and deśe deśe [in every country]”. This might seem terribly
banal and optimistically utopian, yet it is part of a yoga‑oriented,
faith‑based, competitive diplomatic, soft power initiative. Evidence of
this includes propositions such that Yoga and Sanskrit can solve cli‑
mate change (Chauhan 2015; King 2015; Jacobs 2016; United Nations
India 2019; Miller 2020). The final aspiration of Samskrita Bharati,
however, is evidenced through its road map, which aims to build on
simple Sanskrit (saṃskṛtaṃ saralam) utterances toward it being spo‑
ken all the time (saṃskṛtaṃ sarveṣām). This potentially leads to an
14 Sanskrit and Yoga are used to brand the nation (McCartney 2021a). The produc‑
tion of legitimacy and authority in diplomatic and economic arenas involves interweav‑
ing narratives involving a product, a place, and a nation (Aroncyzk 2013) through which
nations work to control their own images by implementing strategic communication
strategies (Ermann, Hermanik 2018). This narrative is only a few clicks away from con‑
firming one’s bias. The following quote, from Soumitra Mohan (2020), encapsulates the
sentiment around its didactic potential: “The language deserves to be treated much
better than it has been so far, more so when it has been called the best ‘computerable’
language. Sanskrit’s credentials to be a language of future India are definitely better
and greater than we have realised so far. Its revival will not only renew and revive the
pride in our own cultural heritage but will also bring about spiritualism and the con‑
cept of a meaningful society and polity, thereby bringing order and peace all across
the country, a desideratum for any developed society”. A similar sentiment comes from
Sampūrṇānanda Saṁskṛta Viśvavidyālaya (SSV)’s homepage (2019) (https://ssvv.
ac.in/brief‑history). SSV is one of India’s best‑known Sanskrit universities, which is
located in Benares, Uttar Pradesh. SSV explains on its homepage that “Sanskrit is the
most ancient and perfect among the languages of the World. Its storehouse of knowl‑
edge is an unsurpassed and the most invaluable treasure of the world. This language
is a symbol of peculiar Indian tradition and thought, which has exhibited full freedom
in the search of truth, has shown complete tolerance towards spiritual and other kind
of experiences of mankind, and has shown catholicity towards universal truth. This
language contains not only a rich fund of knowledge for people of India, but it is also
an unparalleled way to acquire knowledge and is thus significant for the whole World”.
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unavoidable critical mass (saṃskṛtaṃ anivāryam), which will inev‑
itably lead to a language shift (saṃskṛta sarvatra), and adoption of
the new global lingua franca (viśva bhāṣā) (McCartney 2017e). The
perceived net‑positive outcome (abhyudaya) has India positioned as
the next global superpower and paragon of moral virtue, its ultimate
dispenser (viśva‑guru) (Bharati 2014; Singh R.K. 2014; Press Trust
India 2018; 2019).
3 Comparing 2001 and 2011 Census Results
Now, it is time for some bookkeeping (pusta pālana). This section pro‑
vides a straightforward analysis of the 2001 and 2011 census results.
The Persons category is further disambiguated by two binaries, Ru‑
ral/Urban and Males/Females. In the 2011 result (n = 24,821), fewer
L1‑Sanskrit tokens were returned from Rural areas (10,908), as op‑
posed to Urban areas (13,913). This gives a ratio of 44:56. However, Bi‑
har completely reverses this with an 89:11 ratio in favour of rural are‑
as. See [tab. 2] for a comparison of the 2011 top ten Rural:Urban states.
Table 2 Rural and Urban Top Ten States, 2011 (Office of the Registrar General 2020)
2011 Urban Top 10 2011 Rural Top 10
Bihar 3,041 Maharashtra 3,555
Rajasthan 1,461 Uttar Pradesh 1,668
Uttar Pradesh 1,394 Madhya Pradesh 1,020
West Bengal 1,066 Karnataka 1,016
Himachal Pradesh 857 Rajasthan 914
Madhya Pradesh 851 Tamil Nadu 743
Goa 385 Gujarat 680
Odisha 306 Goa 670
Jharkhand 264 NCT of Delhi 594
Maharashtra 247 Jharkand 589
The sex difference splits 55:45. A total of 13,636 Μale tokens were
returned compared to 11,185 Female tokens. Every state/union ter‑
ritory has more Males to Females at a 60:40 average. However, Ta‑
mil Nadu has a 50:50 split and Puducherry (Pondicherry) is the on‑
ly instance where Males are fewer than Females at 29:71 (Office of
the Registrar General 2020); table 3 compares the L1‑L3 (total) ‘San‑
skrit speakers’ between the 2001 and 2011 censuses [tab. 3]. Self‑re‑
ported L1 speakers increased from 14,135 to 24,821; the L2 figure
has stayed almost the same, while the L3 figure has dropped by 48%.
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Table 3 2001‑2011 Sanskrit L1‑L3 (Office of the Registrar General 2020)
L1 L2 L3
2001 14,135 1,234,931 3,742,223
2011 24,821 1,134,362 1,963,640
% change 43 % ‑9 % ‑48 %
We can still use these data to locate sub‑district administrative zones
which have the highest numbers. Table 4 elaborates on the previous
table, demonstrating that even though the total number of L1 rose
between 2001‑11 the total L3 has almost halved [tab. 4]. This sug‑
gests that the total number of L1‑L3 for 2011 decreased by 37%, even
though the 2011 L1 increased by 76%.
Table 4 L1‑L3 Sanskrit 2001 and 2011 (Office of the Registrar General 2020)
2001 Total 2001 Total % Change
L1 14,135 24,821 43%
L2 1,234,931 1,134,362 ‑8%
L3 3,742,223 1,963,640 ‑48%
L1‑L3 4,991,289 3,122,823 ‑37%
Male L1 8,189 13,636 67%
L2 875,107 713,772 ‑18%
L3 2,751,121 1,266,098 ‑54%
L1‑L3 3,634,417 1,993,506 ‑45%
Female L1 5,946 11,185 47%
L2 359,824 420,590 14%
L3 991,102 697,542 ‑30%
L1‑L3 1,356,872 1,129,317 ‑17%
Another significant point relevant across the L1‑L3 range relates to
the relationship between Hindi, English and Sanskrit. The reason the
L2‑Sanskrit figures are different between table 4 and table 5 is due to
table 4 consisting of all the L2‑Sanskrit speakers [tab. 4]. In contrast,
table 5 shows only the L1‑Hindi_L2–Sanskrit and L1‑Hindi_L2‑English
figures [tab. 5]. This figure is significant, as 95% of L2‑Sanskrit speak‑
ers are L1‑Hindi speakers (1,174,019 / 1,234,931).15 This locates the
L2‑Sanskrit phenomenon within an exceptionally Hindi‑centric con‑
15 The Hindi language category consists of 57 sub‑languages and dialects (Office of
the Registrar General 2020).
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text. This is similar to Breton’s (1976, 304) observation based on the
1961 census, that “Le centre de la connaissance du sanskrit à notre
époque est de loin la plaine gangétique (Uttar Pradesh: 79,000, Bi‑
har: 29,000, Punjab et Haryana: 20,000, Delhi: 9,000)”. However, it
is important to appreciate that this group only comprises 0.3% of the
total number of L1‑Hindi speakers. The Male figures for both L2‑San‑
skrit and L2‑English have fallen (24 and 11%) while the Female fig‑
ures have increased (6 and 19%). The Totals have respectively de‑
creased 15 and 1.2%.
Table 5 L1‑Hindi_L2‑Sanskrit/English between 2001 and 2011 (Office of the
Registrar General 2020)
L TOTAL Male Female
2001 Sanskrit 1,174,019 830,827 343,192
English 32,399,287 21,931,407 10,467,880
2011 Sanskrit 994,863 631,099 363,764
English 32,018,890 19,592,236 12,426,654
Table 6 begins with the 2011 Total Persons figures for L1‑Sanskrit
[tab. 6]. Below, in the next part of the table the L1‑Sanskrit_L2‑Hin‑
di_English combination equates to 69% of the total L1‑Sanskrit_L2‑α
figure. In the bottom part of the table the combined L1‑Sanskrit_
L2‑α_L3‑Hindi_English portion is 77%. These data show the intimate
relations that Hindi and English have with Sanskrit.
Table 6 2011 L1‑Sanskrit_L2‑[Hindi‑English]_L3[English‑Hindi] (Office of the
Registrar General 2020)
TOTAL Male Female
L1‑Sanskrit 24,821 13,636 11,185
L2 19,712 11,075 8,637
L2 Hindi 12,221 6,960 5,261
L2 English 1,347 727 620
H+E Total 13,568 7,687 5,881
H+E % 69 69 68
L3 7,910 4,600 3,310
L3 Hindi 2,267 1,327 940
L3 English 3,796 2,211 1,585
H+E Total 6,063 3,538 2,525
H+E % 77 77 76
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Table 7 below presents data related to L1‑Sanskrit_L2‑α [tab. 7]. It
shows Hindi’s clear L1‑Sanskrit_L2‑α majority with 62% of the L2
category.16 While Hindi is one of India’s official languages (along‑
side English, which also ranks high), the data show the intimate re‑
lation with the Hindi heartland. Notice that Female L2‑Odia tokens
were higher than Male (180:132), as well as Konkani (39:37), and
Others (83:76).
Table 7 L1‑Sanskrit/L2‑α rankings, 2011 (Office of the Registrar General 2020)
L2 TOTAL Male Female
Hindi 12,221 6,960 5,261
Marathi 1,934 1,071 863
English 1,347 727 620
Bengali 900 462 438
Kannada 839 502 337
Tamil 551 281 270
Gujarati 365 254 111
Urdu 325 193 132
Odia 318 138 180
Telegu 271 150 121
Malayalam 163 86 77
Konkani 159 76 83
Others 76 37 39
Table 8 shows the fluctuations between the dominant Sanskrit states
by comparing the results from the 2011 and 2001 censuses [tab. 8].
What might explain Uttar Pradesh’s fewer speakers and Maharash‑
tra’s increase?
Table 8 2011 and 2001 State‑level L1‑Sanskrit Census Results (Office of the
Registrar General 2020)
2001 2011 % change
Maharashtra 408 3,802 832
Bihar 754 3,388 349
Uttar Pradesh 7,048 3,062 ‑57
Rajasthan 989 2,375 140
Madhya Pradesh 381 883 132
Karnataka 830 1,218 47
16 Note: this list is only a portion of the total.
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Did all the speakers from Uttar Pradesh move to Mumbai? How can
the dramatic rise in states like Rajasthan, Madhya Pradesh, and Kar‑
nataka be explained? These data show that the Sanskrit‑speaking
sentiment predominates in the Hindi belt. Having provided some na‑
tional level statistics, what follows is a closer look at these top‑rank‑
ing states, pinpointing L1‑L3 Sanskrit tokens down to district and
sub‑district administrative levels. This begins in Maharashtra.
4 An Explication of Census Data in Several States
4.1 Maharashtra
Table 9 shows the top ten districts in the state [tab. 9]. Making sense of
all the data is challenging because there is an overwhelming amount
of overlap between tables. For ease of comprehension, table 9 is a
modified version of the original. Several columns have been delet‑
ed.17 Respectively, both Pune District (28%) and Pune City Sub‑dis‑
trict (22%) represent the highest L1‑Sanskrit administrative zones
in their category for the state. It is clear from the Urban 3554:Ru‑
ral 145 ratio that 96% of Maharashtra’s Sanskrit tokens are locat‑
ed in urban areas.
Table 9 2011 Maharashtra C‑16 Sanskrit–Top 10 Districts (Office of the Registrar
General 2020)
C‑16 POPULATION BY MOTHER TONGUE
State Code – 27 / Mother Tongue Code – 17 / Mother Tongue Name – Sanskrit
District code Area name Total Rural Urban
P M F P M F P M F
000 MAHARASHTRA 3,802 1,984 1,818 247 145 102 3,555 1,839 1,716
521 Pune 1,091 567 524 51 33 18 1,040 534 506
17 As an example, before the token numbers are given, on the right of each table, the
complete line for Pune District would read, C0116 (table code, denotes that these da‑
ta are from the C‑16 ‘mother tongue’ table), 027 (state code), 521 (district code), 0000
(sub‑district code), Pune (area name), 017000 (mother tongue code), Sanskrit (mother
tongue name). This would look like the following, C0116‑027‑521‑0000‑Pune‑017000‑
Sanskrit. Where it gets confusing is when districts, sub‑districts, and towns have the
same or similar names and coding. For example, the district of Pune (27‑521‑00000) is
similar to its sub‑district constituent, Pune City (27‑521‑04194). The same logic applies
to every other district/sub‑district across the entire suite of census tables. Another ex‑
ample is Nashik District (27‑516‑00000), which has a similarly named sub‑district, Na‑
shik (27‑516‑04152). This raises some methodological issues. We can use these fields
to find all sub‑districts in each state and rank them. We can also filter just the districts
and rank them in the same way.
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C‑16 POPULATION BY MOTHER TONGUE
State Code – 27 / Mother Tongue Code – 17 / Mother Tongue Name – Sanskrit
District code Area name Total Rural Urban
517 Thane 710 385 325 14 9 5 696 376 320
518 Mumbai Suburban 556 263 293 0 0 0 556 263 293
516 Nashik 442 239 203 21 12 9 421 227 194
505 Nagpur 195 98 97 6 6 0 189 92 97
519 Mumbai 109 54 55 0 0 0 109 54 55
511 Nanded 61 30 31 5 2 3 56 28 28
515 Aurangabad 55 29 26 5 3 2 50 26 24
514 Jalna 51 27 24 47 24 23 4 3 1
504 Wardha 42 21 21 22 10 12 20 11 9
Table 10 shows the L1‑L3 relations found in the C‑17 tables [tab. 10].
In particular, the relations between the state language, Marathi, with
Hindi, English, and Sanskrit are located. While Sanskrit clusters with
Hindi and English, at the state level it becomes a bit more complicat‑
ed since it is important to consider the relevant state language in this
clustering. Hindi and English, however, still have an overwhelming
presence. The left column shows L1‑Marathi at the national level,18
the middle column shows how many of these returned L2‑Hindi, while
the right column shows the figures for L3‑Sanskrit. This repeats for
each line demonstrating the L1‑Marathi_L2‑α_L3‑β scenarios. Using
the same formula, the second part of the table zooms in to the state
level figures. L1‑Marathi_L2‑Hindi_L3‑α equates to 42% of the L2 cat‑
egory. The final part of this table focuses on L1‑Sanskrit_L2‑α_L3‑β.
Table 10 2011 Maharashtra C‑17 Bi‑/Trilingualism (Office of the Registrar General
2020)
Marathi across India
L1 L2 L3
Marathi 83,026,680 Hindi 34,650,142 Sanskrit 57,070
Kannada 1,468,221 Sanskrit 559
English 1,395,659 Hindi 870,985
Kannada 26,907
Sanskrit 13,142
Gujarati 361,327 Sanskrit 238
Khandeshi 292,555 Sanskrit 124
Konkani 98,318 Sanskrit 168
18 Notice C17‑0000_2011 compared to C17‑2700 in the middle and right panels, re‑
spectively. The state code for Maharashtra is 2700 and the national code is 0000.
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Sanskrit 56,360 Hindi 22,477
English 19,780
L1‑Marathi in Maharashtra
L1 L2 L3
Marathi77,461,172 Hindi 32,660,911 Sanskrit 54,500
English 1,202,810 Sanskrit 12,673
Kannada 512,117 Sanskrit 471
Khandeshi 292,035 Sanskrit 124
Telegu 150,921 Hindi 31,881
Sanskrit 38
Gujarati 60,552 Sanskrit 142
Sanskrit 54,100 Hindi 21,474
English 19,415
L1‑Sanskrit in Maharashtra
L1 L2 L3
Sanskrit3,802 Hindi 1,782 English 888
Marathi 365
Marathi 1,259 Hindi 598
English 306
English 334 Marathi 49
This demonstrates that the L1‑SOL_L2_L3 cluster with Hindi_English
is a predictor for the relative number of L2 and L3 Sanskrit speakers.
This is consistent across every national and state‑level enumeration.
If we reverse the order (right panel) and begin with L1‑Sanskrit, the
numbers for L2_L3 also follow a similar order, with the State Offi‑
cial Language (SOL), Hindi, and English in superior positions com‑
pared to other possibilities.
Figure 2 2011 Maharashtra: Districts L1‑Sanskrit. (India 2020)
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Figure 2 demonstrates the 2011 District‑level L1‑Sanskrit figures for
Maharashtra [fig. 2]. The top five districts are Pune 1091, Thane 710,
Mumbai Suburban 555, Nashik 442, and Nagpur 195.
Figure 3 2011 Maharashtra: Sub‑districts L1‑Sanskrit. (India 2020)
Figure 3 zooms down to the sub‑district level to show the top five
districts in more detail [fig. 3]. Notice how Nagpur District has been
superimposed in the red box. Next, we move onto the state of Bihar.
4.2 Bihar
In Bihar, the highest number of L1‑Sanskrit tokens are located in the
eastern administrative area of Kishanganj District (210). The top five
districts are listed in [tab. 11].
Table 11 2011 Top 5 Districts: Bihar (Office of the Registrar General 2020)
C‑16 POPULATION BY MOTHER TONGUE
State Code – 10 / Mother Tongue Code – 17 / Mother Tongue Name – Sanskrit
District code Area name Total Rural Urban
P M F P M F P M F
000 BIHAR 3,388 1,845 1543 3,041 1,654 1387 347 191 156
210 Kishanganj 1,028 543 485 962 507 455 66 36 30
212 Katihar 604 324 280 598 321 277 6 3 3
211 Purnia 574 326 248 544 309 235 30 17 13
209 Araria 383 220 163 381 219 162 2 1 1
230 Patna 119 67 52 4 3 1 115 64 51
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From within these districts, Bihar’s top ten sub‑districts are Dighal‑
bank 558 (Kishanganj District), Terhagachh 307 (Kishanganj Dis‑
trict), Baisi 246 (Purnia District), Azamnagar 154 (Katihar District),
Sikti 120 (Araria District), Dagarua 108 (Purnia District), Palasi 105
(Araria District), Falka 92 (Katihar District), Thakurganj 83 (Kis‑
hanganj District), and Patna Rural 82 (Patna District). In [figs 4‑5] no‑
tice the clustering in the far east of the state across four districts.
Figure 4 2011 Bihar: Districts L1‑Sanskrit (India 2020)
Figure 5 2011 Bihar: Sub‑districts L1‑Sanskrit (India 2020)
Unlike Maharashtra, 90% of Bihar’s L1‑Sanskrit tokens are Rural.
Where might they be located? The ‘village‑level’ C‑16 tables are not
available. One cumbersome triangulation method requires scrutinis‑
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ing other tables. The state’s highest returning district is Kishanganj.
Beginning with the ‘town level’ C‑16 table for Bihar, we learn that
Kishanganj Nagar lists 66 Urban L1‑Sanskrit tokens (Office of the
Registrar General 2020). We can combine this with the Village Di‑
rectory of Kishanganj District, Bihar (Office of the Registrar Gener‑
al 2020).19 The relevant code for Dighalbank’s Block is 002. We can
sort and filter all the listed towns and villages with this code and then
sort further for all the places with a population under 5,000 inhabit‑
ants (the town/village population boundary). While we currently are
unable to locate with more accuracy, we are, nonetheless, left with a
list of ‘rural villages’ from which Bihar’s highest L1‑Sanskrit sub‑dis‑
trict is potentially comprised of. Let us move on to Madhya Pradesh.
4.3 Madhya Pradesh
Madhya Pradesh returned more L1‑Sanskrit Urban tokens (54%) [Ru‑
ral 851 (451 M/400 F) and Urban 1020 (537 M/483 F)]. This further
complicates the fabled ‘Sanskrit‑speaking’ village narrative. How‑
ever, the highest‑ranking sub‑district, Pipariya, accounts for 96%
(Rural 485/Urban 5) of Hoshangabad District’s total 524 (496 Ru‑
ral/28 Urban) (Office of the Registrar General 2020). Compared to
the state Rural total, Pipariya Sub‑district equates to 57% of all the
367 sub‑districts in Madhya Pradesh and 26% of the state’s total. At
the village level this can be narrowed down to 114 villages in Pipari‑
ya Sub‑district (Office of the Registrar General 2020).
If this sub‑district does have such a high number of Sanskrit speak‑
ers it is certainly unclear as to why these places are not as famous
as the three so‑called ‘Sanskrit‑speaking’ villages (Jhiri, Sarangpur
Sub‑district, Rajgarh District; Mohad, Gadawara Sub‑district, Narsim‑
hapur District; and Baghuwar, Kareli Sub‑district, Narsimhapur Dis‑
trict). What is more curious is the fact that the districts these three
‘Sanskrit‑speaking’ villages are located in barely returned any L1‑San‑
skrit tokens. The internet contains countless sites that assert that eve‑
ryone, or nearly everyone, in these villages speaks Sanskrit. The dis‑
trict and sub‑district L1‑Sanskrit tokens are represented in [figs 6‑7].
19 Kishanganj District is comprised of seven ‘blocks’, which is the same number of
sub‑districts. The difference between a block and a sub‑district is its function. A block
is a geographical unit for rural development, whereas a sub‑district (tehsil) is a geo‑
graphical unit for revenue collection (Maheshwari 1984).
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Figure 6 2011 Madhya Pradesh: Districts L1‑Sanskrit. (India 2020)
Figure 7 2011 Madhya Pradesh: Sub‑districts L1‑Sanskrit. (India 2020)
Like Bihar, filtering through the village/town lists for Pipariya
Sub‑district the towns with 5,000+ inhabitants can be removed.
The result is 142 villages, ranging in size from 4,767 (Khapar Khe‑
da) down to two (Pathi Thekredri) inhabitants. It is this list that the
majority of Madhya Pradesh’s Sanskrit tokens come from (Office of
the Registrar General 2020).
The ST‑15 (Scheduled Tribes) table is a subset of the C‑16 tables
relating to Scheduled Tribes’ mother tongues. These are available at
the state/district levels. 6.7% of the L1‑Sanskrit state total (149/1871)
is comprised of people who identify as members of Scheduled Tribes.
Of this, 126 tokens are from Hoshangabad District (Office of the Reg‑
istrar General 2020).
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Table 12 2011 and 2001 Madhya Pradesh L1‑Sanskrit (Office of the Registrar
General 2020)
Total Persons – Sanskrit L1 L2 L3
2011 1,871 246,940 454,245
2001 381 210,400 960,176
% change 391 17 ‑53
Table 12 scratches beneath the surface to show the changes between
2001 and 2011 across the L1‑L3‑Sanskrit range [tab. 12]. This figure
reflects the national data. As we have discussed, the L1 change is
aspirational. It really makes not much sense, otherwise. How could
a 391% increase have occurred in just one decade? The L2 figure is
more feasible, however the L3 decline of 53% is a worrying predic‑
tor for the vitality of Sanskrit. Could it be that all the Sanskrit village
mythology circulating might be harming Sanskrit’s role? In relation
to the Hindi/English/Sanskrit trinity, in Madhya Pradesh L1‑H_L2‑E_
L3‑S comprises 98% of all the L3‑Sanskrit possibilities. This decline
is also considerable among the Scheduled Tribes of Madhya Pradesh.
Table 13 highlights the changes of L1‑Bhili/Bhilodi_ and L1‑Gondi_
L2‑α_L3‑Sanskrit [tab. 13]. Both have declined dramatically between
2001 and 2011.
Table 13 2011 and 2001 Madhya Pradesh L1‑ST_L2‑α_L3‑Sanskrit (Office of the
Registrar General 2020)
2011 2001 % change
L1‑Bhili/Bhilodi_L2‑α_L3‑Sanskrit 779 1,677 ‑54
L1‑Gondi_L2‑α_L3‑Sanskrit 661 889 ‑26
Madhya Pradesh’s 2011 L2‑Sanskrit total is 246,940. This is com‑
prised of the Scheduled Tribes’ total of 13,540 (5% of state total).
This 13,540 is predominated by 84% Rural tokens. Of this Scheduled
Tribes’ total 52% come from a group of 60 ST‑L1 languages, including
Gond, Arakh, and Agaria (prevalent in Hoshangabad District). The
next group of languages include Bhil and Bhilala (15%), and Kol (10%)
(Office of the Registrar General 2020). Having located the districts
and sub‑districts within Madhya Pradesh where L1‑L3 Sanskrit to‑
kens were returned, a clearer image of where future fieldwork could
be directed emerges. The final state is Uttar Pradesh.
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4.4 Uttar Pradesh
Uttar Pradesh is India’s most populous state with 199,581,477 people
(Office of the Registrar General 2020). While Uttar Pradesh experi‑
enced a 57% decrease in L1‑Sanskrit tokens, in comparison, the total
nationwide increase for L1‑Sanskrit is 76% (Government of Office of
the Registrar General 2020). What has caused Uttar Pradesh to de‑
crease when other states witnessed large increases? Three districts
are worthy of closer scrutiny because of how they changed dramat‑
ically between 2001 and 2011. The state capital, Lucknow, reduced
by ‑82%, while Unnao reduced by ‑95%, and Gorakhpur, the elector‑
ate of UP’s Chief Minister, Yogi Adityanath, decreased by ‑99% (Of‑
fice of the Registrar General 2020). The top ten districts are Kanpur
Nagar 932, Sitapur 722, Sultanpur 323, Ghaziabad 128, Saharanpur
85, Ballia 79, Lucknow 55, Varanasi 55, Bijnor 50, and Agra 41 (Of‑
fice of the Registrar General 2020); figure 8 provides the total Per‑
son numbers for each district [fig. 8].
Figure 8 2011 Uttar Pradesh: Districts L1‑Sanskrit. (India 2020)
Figure 8 shows the numbers for each district in which L1‑Sanskrit to‑
kens were returned. In Uttar Pradesh, 1,697 Male L1‑Sanskrit tokens
were returned compared to 1,365 Female. Like Madhya Pradesh and
Maharashtra, the Urban L1‑Sanskrit (1668) token count is slightly
higher than the Rural equivalent (1394). The urban area of Varanasi
(Benares), which is considered one of the holiest cities of Hinduism,
which is home to the famous Sanskrit university, Sampūrṇānanda
Saṁskṛta Viśvavidyālaya (SSV), only returned 54 tokens (36 M/18
F). Similarly, Breton (1976, 306) wonders why the famous tradition‑
al seats of Sanskrit learning have fewer speakers of Sanskrit. No‑
tice that Kanpur is the city with the highest number of returned
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L1‑Sanskrit tokens (Office of the Registrar General 2020). The top ten
sub‑districts are Kanpur 931, Mahmudabad 482, Lambhua 310, Gha‑
ziabad 127, Sidhauli 94, Biswan 83, Ballia 62, Varanasi 55, Deoband
51, and Bijnor 50 (Office of the Registrar General 2020). Kanpur is
also the highest ranked town. Zooming in, figure 9 shows the unique
L1‑Sanskrit results for each of the six tehsils in Sitapur District [fig. 9].
Figure 9 2011 Sitapur District within Uttar Pradesh. (India 2020)
In 2001, Sitapur District, Uttar Pradesh (430 kilometres east of New
Delhi), reportedly had the highest number of all the districts in the
country, at 558 (Priyanka 2014). The 2011 total of 722 (M 378/F
344) is a 28% increase. Sitapur District also represents 24% of the
state’s total. It splits Rural 1275 (M 676/F 599) and Urban 73 (M 33/F
40). This means that the district of Sitapur provides 46% of Uttar
Pradesh’s L1‑Sanskrit tokens, which, itself, is comprised of 90% Ru‑
ral from across the district’s six tehsils (Office of the Registrar Gen‑
eral 2020). When compared with the 2001 results for the same the
district the fluctuations are quite remarkable. Where did 2,604 San‑
skrit ‘speakers’ from Biswan tehsil go? Sitapur District has the sec‑
ond highest L1‑Sanskrit number in Uttar Pradesh.
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Figure 10 2001 and 2011 Sitapur District: Sub‑districts L1‑Sanskrit. (India 2020)
Figure 10 shows the 2011 figures for each tehsil of Sitapur District,
which indicates that Mahmudabad Tehsil has the most with 482
(M 258/F 224) [fig. 10]; table 14 displays the top five sub‑districts
[tab. 14]. Three of the list are located in Sitapur Tehsil and Biswan
Town is the sixth‑highest ranked in the state, as well as the fifth‑high‑
est ranked tehsil. Both Biswan and Sidhauli tehsils return more Fe‑
male than Male tokens. While Lambua returns the same number for
both sexes.
Table 14 2011 Top 5 Rural Tehsils (Office of the Registrar General 2020)
Tehsil Total Male Female
Mahmudabad 482 258 224
Lambhua 310 155 155
Sidhauli 94 49 45
Ballia 62 32 30
Biswan 83 39 44
In contrast to Kanpur, Mahmudabad Tehsil (Rural) is the second high‑
est tehsil in the state with 482 (258 M/224 F). If all the L1‑Sanskrit
‘speakers’ do not live in towns then is it safe to assume they live in
villages? Mahmudabad Tehsil has 341 villages (Office of the Regis‑
trar General 2020). The question is, in which villages are L1‑San‑
skrit ‘speakers’ living?
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Table 15 2011 Religious‑Political affiliations and Literacy‑Sex ratio comparisons
(Office of the Registrar General 2020)
State Tehsil name Population Literacy Sex ratio Political preference Hindu %
MP Pipariya 181, 261 63.8 896 BJP 95
MP Sarangpur 186,082 56.4 950 BJP 84
UP Kanpur 3,470,334 72.8 860 BJP 83
MP Indore 2,389,511 73.6 925 BJP 74
UP Mahmudabad 596,252 47.1 884 Samajawada 74
MP Huzur 2,107,523 72 920 BJP 72
Finally, table 15 lists some of the main tehsils mentioned above
[tab. 15]. They are ranked, first, by the percentage‑age of Hindus in
each tehsil. Most display a preference for the Bharatiya Janata Party
(BJP), regardless of the size of the Hindu majority. The curious thing
is that some of the highest L1‑Sanskrit tehsils in Madhya Pradesh and
Uttar Pradesh return literacy and sex ratios well below national and
state averages. What does this tell us about the ability of Sanskrit
to ‘transform lives’ and the development grand narrative it serves?
5 Concluding Remarks
This paper compares the 2001 and 2011 Sanskrit census results pay‑
ing closer attention to the top‑ranking states Maharashtra, Bihar,
Madhya Pradesh and Uttar Pradesh. However, the results of this
study are unexpected. Further analysis across the remaining states
will be released in forthcoming articles. Still, we are able to deter‑
mine that Maharashtra returned the highest number for L1‑Sanskrit;
that most of the L1‑Sanskrit speakers live in urban areas; that the
‘Sanskrit‑speaking’ village is an aspirational myth not borne out in
the government data; that more men claim to speak Sanskrit; that
the overwhelming majority also speak Hindi and English, regard‑
less of L1‑L3 combinations; that the L1‑Hindi/L2‑Sanskrit combina‑
tion amounts for 92% of the total L2‑Sanskrit speakers; and that, re‑
gardless of the rhetorical and ideological bluster, Sanskrit continues
to fall short of its alleged capacity for attaining the #Sanskrit4Cli‑
mateAction goals related to key indicators, such as sex, literacy, and
health development.
Sanskrit, alongside Yoga, is a key instrument for branding the nation.
This is a domestic as well as international project that has a symbiot‑
ic relation to the global wellness and leisure markets, which is fertile
ground for cultivating banal nationalism. From a language acquisition
perspective, the media’s preference to provide pithy and inaccurate da‑
ta from the census seems counterproductive, if not misplaced. While
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moods certainly lift with hearing the L1 level rose between 2001 to
2011, the more interesting categories relate to L2 and L3 levels, both
of which have reduced, however the L3 level fell by almost 90%.
With this finer‑grained analysis, a clearer map of where people
who have an affinity to identify as L1‑L3‑Sanskrit speakers were lo‑
cated at the last census. Regardless of whether they do in fact speak
Sanskrit, these data will aid future research related to in‑country
field work, enabling strategic sorties down to the sub‑district tehsil
level. Finally, the 2021 Indian census will the first digitised cen‑
sus the nation will embark on. Hopefully, this allows for data to be
enumerated, rationalised, and published much sooner than the sev‑
en‑year lag that occurred at the last census. Unlike the botched 1941
census, which first introduced self‑reporting of data, it is anticipated
that this new age of demography in India will not suffer the same fate.
From a linguistic perspective, building on demographic data potenti‑
ates future exploration of various aspects of language revitalisation
and second‑language acquisition through in‑depth study of particu‑
lar linguistic features related to substrate interference and imper‑
fect learning of the target language.
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