This agreement represents the complete agreement concerning this license between the parties and supersedes all prior agreements and representations between them.
The Licensor hereby grants license to the Licensee to use the Licensed Software for the License Period.
It is Agreed, Confirmed and Declared that the license to use the Licensed Software are at all times, subject to the following terms and conditions agreed upon between the Licensee and the Licensor that:
The Licensee shall use the said software entirely at his/her/its own risks and that the Licensor shall under no circumstances be liable for any losses or damage including the following (whether such losses were foreseen, foreseeable, known or otherwise):
In the event the Licensee either directly or through any sister concern, association, agent, assign or through any person claiming through or under the Licensee or through any other third party does any of the following acts then in that event the Licensee shall pay the Licensor a sum of two times the subscription amount as Liquidated damages. Both the parties herein agree that the said amount of damages would be suffered by the Licensor on account of the said breach and the said amount is a genuine pre-estimate of damages.
Without prejudice to whatever is stated hereinabove, during the continuation of this Agreement and thereafter, the Licensee shall indemnify and keep indemnified the Licensor and the Surveyor against any loss/damage/ costs/ consequence/ claim that would be suffered or is suffered due to any improper, incorrect or impermissible use of the IRS, whether in whole or in part, whether direct or indirect by the Licensee or his agents/servants/subordinates/clients.
This Agreement may be amended only by a written Agreement
This Agreement and its Terms and Conditions shall be governed by and construed in accordance with Indian law.
Any forbearance or delay by the Licensor in enforcing any provisions of these terms and conditions of this Agreement or any of its rights under this Agreement shall not be construed as a waiver of such provision/s or its rights thereafter to enforce the same.
The Licensor may, in their sole discretion, interalia in the following cases terminate this Agreement:
The Licensor’s performance under this Agreement is subject to interruption and delay due to causes beyond its reasonable control such as acts of God, acts of any Government, war or other hostility, civil disorder, the elements, fire, explosion, power failure, failure of the Internet and other networks beyond the control of the Licensor, equipment failure, industrial or labour dispute, inability to obtain essential supplies and the like.
The IRS is a collaborative study serving the research needs of the members of the MRUC. As such, it is desirable that the IRS data is used responsibly by all the member-subscribers and hence the need for a self-regulating code for use of the IRS data. The Code is to be read along with the IRS End Users License Agreement released with IRS 2019Q4 which is binding on all Subscribers. The Code for self-regulation is to provide for
a)Common understanding of research terms, data definition and data analysis norms as provided by MRUC, including the statistical rules governing the IRS (Appendix I);
b)Adherence to data analysis and reporting norms for truthful representation of data to clients, readers of the publication and the public at large (Appendix I);
c)Redressal mechanism for complaints received in respect of data misrepresentation, abusing/disregarding set statistical norms and/or any other data usage provided by this Code.
Any claim or comparison for publicity/promotion, hoardings or communication in any other form which is in violation of the protocols laid down in para B below will be subject to adjudication as per the redressal mechanism.
The IRS 2019 Q4 data is licensed to the IRS Subscriber for a period of two years and as such the IRS data can only be used by registered subscribers of the data. MRUC retains the right to initiate legal action against any access or unauthorized use of the data by non-subscribers and any unauthorized sharing of the data by any subscriber.
B. Code of Self-Regulation
a) Comparisons with previous rounds
b) Use of IRS2019Q4 data in publicity and promotions
In all cases of publicity/promotion, hoardings or communication in any other form, where Readership / Listenership / Viewership data may be compared with two or more publications / radio stations / TV channels / any other media, users should abide by the following protocol:
Any claim for “leading”, “No.1” or to establish top position by any parameter/s should ONLY be based on a like to like comparison, i.e. the same set of readership / listenership / viewership data to be compared amongst publications / radio stations / TV channels / any other media, sourced only from IRS 2019Q4.
Comparison should be restricted to publications of similar publishing frequencies, i.e., Daily newspapers to Daily newspapers, weekly newspapers to weekly newspapers and magazines to magazines.
Comparison should be between similar readership frequencies, and restricted to any one of the pre-defined metrics – i.e. AIR to AIR, Upto 3 days to Upto 3 days, Upto 7 days to Upto 7 days and TR to TR.
For any specific demographic, geographic, product profile category the comparison should be done with the same set of comparable readership / listenership / viewership numbers for all publications / radio stations / TV channels / any other media.
The applicable parameter/s along with the specific geographical area (City, State, Country) must be clearly mentioned (in the same font size as the headline) in the publicity material.
c) Variant readership
The “main” edition and the “variant” edition should be treated as two different newspapers
Media planners should verify readership being used for comparison between publications, i.e., Main or Variant, and ensure like-to-like comparisons are used for selection of publications
Readership numbers of Main issue of one publication should be compared only with the Main issue readership numbers for other publications.
For any cost comparisons, it is essential to verify whether the right rates, from the Main issue or Variant issue rate cards, are being used for all selected publications to ensure no incorrect comparisons are made.
C. Redressal mechanism
Any violation under this Code by any subscriber/member/user, will be adjudicated by a Disciplinary Committee (DisCom) constituted by the MRUC.
contravening theCode, DisComwillproposefollowing corrective action against the offender, which may include:
The said publication to print a corrigendum on the same page and size of the publicity in case of publicity/campaign in anewspaper and/or magazine (text of corrigendum as advised by MRUC)
In case of any other form of publicity/campaign, then the corrigendum to be published on page 3 in size 20 x 3 cc as per draft of the corrigendum advised by MRUC
Corrigendum to be published within a period of 15 days from the date of decision ofthe DisCom
MRUCmay advise all affected competing publications to publish the same corrigendum on no cost basis.
MRUC may also inform all its members about the said violation.
Guidelines for Responsible Use of IRS Data
1) Statistical rules governing IRS 2019Q4
a) IRS 2019Q4 fieldwork period: December 2018 to March 2020
d) For such publications/titles; a separate database has been is provided which has limited geographic variables along with print readership variables such as TR and AIR.
2) Data classification
a) Household vs. Individual data
i)The IRS reports Household data and Individual data separately
ii)Reading Household Consumer Goods and Durables
Penetrationof Durables ownership and purchase of consumer goods is captured at household level and should not be used for universe sizing in the Individual database.
Individual datashould be considered only for consumer profiling. It should be read as the targeted Individuals who own those durables or purchase the respective consumer goods, in their household.
b) Readership data
Readership for Daily Newspapers is now reported by the following metrics-
AIR - Yesterday Readership
1 to 3 days
1 to 7 days
Total Readership – last 4 weeks
ii) Variant Readership
IRS 2019Q4 captures readership for both - main paper as well as variants of the main paper for select markets.
Variants have been identified basis differences in mastheads / presence or absence of supplements and/or price point differences (as reported in ABC or by details as provided by respective publication houses)
Causes for Variations in Sample Surveys
All estimates based on a sample survey are subject to ‘sample variation’. However tightly controlled, the results from one sample of people will differ somewhat from another sample of people drawn in exactly the same way.
Any characteristic (e.g. % owning a cell phone, % reading a newspaper etc.) observed in any sample survey or sample surveys conducted at two different time periods, could show different results. These observed differences can be of two types:
a) Real change has occurred in the characteristic being measured. Such as cell phone ownership may have gone up.
b) No real change has actually happened, but the survey shows some differences.
Obviously, there is no issue in the first case. Let us now focus on the second case. The observed differences can be due to many reasons. These can be classified into three broad groups:
i. First: Sampling Error - Sampling error represents the uncertainty in survey estimates that occurs because we observe data on a sample in the population rather than on every unit of population. Any sample survey, including the best and the largest in the world, will have variations in estimates, simply because it is a sample survey. One can only minimize sampling error by designing samples to provide the most precise estimates at available resources. There is no way to avoid this error other than to conduct a Census. Sampling error is often expressed as standard errors or in simple terms 'Margin of Error‘ (at a design confidence level, for estimates). The magnitude of Margin of Error depends on the incidence of observed characteristic and the sample size. (Refer below the paragraph on Sampling Variations)
ii. Second: The survey design (the theoretical parameters such as representativeness and accuracy of the household selection frame, in our case the electoral rolls, etc.) will have a role to play in this.
iii. Third: Non-Sampling Errors - Lastly, errors creeping in due to non-response, respondent’s understanding of questions, wrong or incomplete responses from respondents, respondent selection processes not followed accurately, interviewer mistakes and errors in data punching or processing etc.
Our objective, is to
a) Operate within the ranges defined by globally accepted random sampling methods (i.e. within ‘First point’ above)
b) Create a robust theoretical design to minimize errors referenced under ‘Second’.
c) Control processes as much as possible such that errors occurring due to ‘Third’ are kept to a minimum.
The level of sampling variation (Margin of Error) is what the survey designers have agreed to accept (indicated by the survey’s reporting standard) for any survey estimate. The IRS reporting standards define that the estimates be reported within 20% Margin of Error at 90% confidence level for an incidence of 10%.
Let’s explain a few related and important points on this:
(i) 90% confidence means that if a survey were to be conducted 100 times, on 90 occasions the variation would be within range defined by the reporting standard. Please note that this means that in 10% cases the estimate may well be beyond the defined range.
(ii) IRS estimates are not point estimates, but a range estimate and the range depends on the 'Margin of Error' associated with each estimate. And as per IRS design statistics, there are 90% chances that the actual estimate lies within this range (lower and upper confidence limit).
(iii) IRS reporting standards define that the estimates be reported within 20% Margin of Error at 90% confidence level for an incidence of 10%. Hence, a higher incidence will have a lower Margin of Error and a lower incidence will have a higher Margin of Error.