The Hindu Editorial with Vocabulary – June 2018

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The Hindu Editorial with Vocabulary – “Data in a Post-Truth Age”

Trust in official statistics is vital for democracy — the new policy must avoid centralisation. David Spiegelhalter, president of Royal Statistical Society in the U.K., gave a most unusual presidential address in 2017. Instead of talking about esoteric statistical techniques, he talked about declining trust in numbers in a post-truth society bombarded by fake news and alternative facts. He recommended to the statistical community that the best way of inspiring trust was to be trustworthy by demonstrating competence, reliability and honesty.

India has been fortunate in inheriting a statistical system from stalwarts like P.C. Mahalanobis and C.R. Rao that has historically demonstrated all three. However, with the growing demand for statistics and increasingly challenging data collection environment, the move by Ministry of Statistics and Programme Implementation (MOSPI) towards developing a National Policy on Official Statistics is most welcome.

There is much to like in this policy. It notes increasing data needs, lays down the groundwork for ethical data collection, highlights the importance of data quality and addresses the need for documentation and durable data storage. However, it also remains rooted within the confines of governmental administrative structures and does not directly address the criteria identified by Mr. Spiegelhalter. In the Indian context, each of these presents great challenge.


Sample surveys, the bedrock of Indian statistical systems, must make explicit choices about who to ask various questions as well as what to ask and how to ask. In a statistical system developed by renownedstatisticians and econometricians, it is not surprising that much attention has been directed towards identifying the universe of respondents and sample selection. However, this is only a small part of the challenge. Given the increasing need for statistics in diverse areas, it is important that scholars from many different disciplines be involved.

The National Sample Survey (NSS) collects data on occupations and industries of workers. In 2009, it suddenly switched from older codes designed in 1968 to new series of codes developed in 2004. This change makes it difficult to differentiate between farmers and farm managers and shopkeepers and sales managers via occupational codes alone. This leaves out such a large portion of the Indian workforce that it is mind-boggling. Why? We decided to adopt international standards developed for industrial societies where self-employed farmers and shopkeepers have been swallowed up by large corporations. I suspect that if a sociologist interested in occupations was involved in overseeing this change, it might not have passed the scrutiny.


How surveys are designed and questions are developed has evolved into a science that transcends the skill set usually employed by our statistical systems. The Reserve Bank of India has adopted an inflation-targeting approach that relies on data on inflation expectations of individuals. In a country where ASER (Annual Status of Education Report) surveys repeatedly document extremely low mathematical skills, how reliable are the data when individuals are asked to compare their expectations of inflation rates over the coming year with that in the future? We have little understanding of reliability and validity of these data, and yet they form the bedrock of our policy. Experiments designed by cognitive anthropologists, educational assessment experts and survey design specialists are needed to arrive at the correct questions. And even then, we will need some way of estimating uncertainty surrounding these results.


The draft policy as well as many other reports have paid great attention to the fact that data collection is increasingly being done by contractual employees and for-profit organisations. Supervising them and ensuring their honesty remains challenging. While improved technology for monitoring fieldwork such as random segment audio recording of interviews and real-time checks for detecting frauds and errors may help increase honesty, there is no substitute for empathy and experience. Whenever I talk about interviewer errors and fraud, I recall doing a health-related interview in a mosquito-infested locality. I was bravely suffering through mosquito bites until my respondent told me her husband was recovering from malaria and I simply wanted to flee her home. We expect interviewers to work under challenging circumstances and often send them out to collect data with little training and support. A nimble survey management structure that understands the difficulties of on-the-ground data collectors and responds appropriately to find ways of ensuring quality and honesty must form the cornerstone of good data collection.

The draft policy on official statistics engages with these challenges only tangentially. Instead, it chooses to follow the report of the C. Rangarajan-led National Statistical Commission (NSC) submitted in 2001 and focusses largely on coordination within different ministries at the Centre and between State governments and the Centre. A tendency to centralise authority and decision-making within well-defined structures such as the NSC forms the core of the policy statement. It also recommends that a registered society under the oversight of MOSPI be set up with Rs. 2,000 crore endowment that will be tasked with all government data collection and statistical analyses.

Instead of creating a statistical data ecosystem that harnesses the energy of diverse institutions and disciplines in which innovative thinking on data collection and analysis could be undertaken, this tendency towards centralisation may well isolate official statistical systems. This is quite a departure from India’s illustrious history. Mahalanobis was instrumental in setting up both the Indian Statistical Institute (ISI) and what was to become the National Sample Survey Organisation. Most of the early innovations implemented in the NSS emerged from work by academics at the ISI. However, as former member of the NSS Governing Council, T.J. Rao, notes, the collaboration between academics and the NSS has weakened substantially in recent years. The proposed move would lead to even further alienation of official statistical systems from the academic and research infrastructure of the nation.

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Harness diverse energies

If we are to revitalise India’s statistical infrastructure, it is vitally important to harness diverse energies from academic and research institutions such as the ISI, the Indian Agricultural Statistics Research Institute, National Council of Applied Economic Research, the Tata Institute of Social Sciences, the International Institute for Population Sciences, the Delhi School of Economics, the Madras Institute of Development Studies and the National Institute of Rural Development and Panchayati Raj. Smaller, technology-savvy private sector organisations may also make important contributions in technology-driven data collection. Around the world, in diverse countries such as China, South Africa, Brazil, the U.K. and the U.S., statistical ecosystems consist of universities, research institutions and government agencies working synergistically. The proposed policy on official statistics is timely and thoughtful but it is also isolationist. Creative thinking about building synergies with diverse communities such as academic and research institutions would strengthen it and reduce the burden on the NSC, leaving it free to devote greater attention to developing quality control parameters and to play an oversight and coordination role.

The phrase ‘figures don’t lie, but liars figure’ seems to sum up the motif of a post-statistics society. A report in The Guardian in 2017 noted declining trust in official statistics around the world and argued that it damages democracy by jeopardising public knowledge and public argument. The draft National Policy on Official Statistics offers a great start fo fostering trust in statistics but enhancing its inclusiveness will go a long way towards encouraging competence, reliability and honesty in public statistics.

Vocabulary Words from The Hindu Editorial

1. Cornerstone(noun) आधारशिला : Something of great importance that everything else depends on.

Synonyms: Foundation, Fundament, Mainstay, Keystone, Basis, Core

Example: A national minimum wage remained the cornerstone of policy.

2. Endowment(noun) अक्षय निधि/ चंदा/दान: Gift of money that is made to an institution such as a school. (It is a gift of money that is made to an institution or community in order to provide it with an annual income.)

Synonym: Donation, Grant, Charity, Alms, Benefaction, Funding

Example:  We could have stopped paying into the endowment at that stage, but another problem with the policies is that the charges are loaded at the front end..

3. Synergy(noun) तालमेल /मिलजुल कर: the interaction or cooperation of two or more organizations, substances, or other agents to produce a combined effect greater than the sum of their separate effects .

Synonyms: Collaboration, Cooperation, Symbiosis, Alliance, Union, Teamwork

Antonyms: Divorce, separation, discord.

Example: Investors have already begun to doubt the potential synergies and question the impact on earnings.

4. Foster(verb) लालन-पालन करना/ प्रोत्साहन देना : To encourage the development or growth of ideas or feelings.

Synonyms: Promote, Encourage, Embolden, Advance

Antonyms: Discourage, Hinder, Inhibit, Suppress, Impede

Example: Weak government damages growth by fostering uncertainty.

5. Jeopardize(verb) ख़तरे में डालना/ आपत्ति में डालना : To put something in danger of loss harm or failure.

Synonyms:  Imperil, Endanger, Menace, Threaten, Hazard

Antonyms: Protect, Safe Guard, Preserve, Shelter

 Example: The 1973 oil crisis and political changes within member states threatened to jeopardize agreement on regional policy.

6. Esoteric(adjective) गुप्त/ जिसे कुछ ही लोग समझ पाएं : Intended for or likely to be understood by only a small number of people with a specialized knowledge or interest. (not openly admitted; private)

Synonyms: Abstruse, Arcane, Recondite, Inscrutable, Cryptic

Antonyms: Exoteric, Comprehensible, Perspicuous, Superficial, Shallow

Example:  There was something about his esoteric interests and unaffected grin that drew me in.

7. Renowned(adjective) सुप्रसिद्ध/ मशहूर : Famous for something. (known or talked about by many people; famous.)

Synonyms: Illustrious, Eminent, Notorious, Famed, Popular, Distinguished

Antonyms: Common, Anonymous, Nameless, Obscure,

Example:  She was renowned for her fine seamstress abilities down through the years.

8. Scrutiny(noun) छान-बीन/ सूक्ष्म परीक्षण/ जांच : The careful and detailed examination of something: (critical observation or examination.)

Synonyms: Perusal, Audit, Probe, Inquisition, Exploration, Inspection

Antonyms: Glimpse, Glance, Cursory Look, Peep, Scan

Example: The small percipient eyes are screwed up, and wrinkled from his repeated minute scrutinies .

9. Transcend(verb) ऊंचा होना/ ज़्यादा होना / पहुंचना : Be or go beyond the range or limits of (something abstract, typically a conceptual field or division).

Synonyms: Eclipse, Surpass, Surmount, Prevail, Outclass, Overcome

Antonyms:  Lose, Fall, Surrender, Fail

Example:  There is nothing that transcends God so nothing is greater than his essence.

10. Nimble(adjective) चालाक/ चतुर/ फुर्तीला : Quick and exact either in movement or thoughts.

Synonyms:  Agile, Quick, Spry, Lissom, Lithe, Dexterous

Antonym: Lumbering, Clumsy, Sluggish, Awkward, Stupid

Example:  He has produced a set of seven steps to keep your mind nimble , steps which may even postpone the onset of dementia, but which at least will probably give your mind a lift.

Word of the Day –  “Pretentious”

  • Transmogrify (verb) आडम्बरयुक्त, कपटी, छली, धूर्त, धृष्ठ, ढीठ, मिथ्याभिमानी
  • Meaning:-  To change or transform into a different shape, esp a grotesque or bizarre one
  • Synonyms:  Transfigure, metamorphose, reorganize, switch over.
  • Antonym: Increase, stagnate, preserve, keep, refuse.
  • Example: In the play, the acter suddenly transmogrified into a monster.
  • उदाहरण: नाटक में कलाकार अचानक से दैत्य में परिवर्तित हो गया।

Quote of the Day

“Every child is an artist; the problem is how to remain an artist once he grows up.” Pablo Picasso

“प्रत्येक बच्चा एक कलाकार होता है, समस्या यह है कि युवा होने पर कलाकार कैसे बने रहा जाए।” पाबलो पिकासो

The Hindu Editorial with Vocabulary Monthly PDF: April 2018

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