Employer-Employee Insurance Scheme is an insurance arrangement between an employer and employee where the employer purchases an insurance policy for the employee. This arrangement benefits both parties as it is based on the principle that the employer has an insurable interest in their employees.

1. Dr. J D Chandrapal
MBA – marketing , PGDHRM, P HD, CII (Award) – London
Development Officer - LIC of India – Ahmedabad - 9825070933

2. EE Scheme – What?
• Employer-Employee Insurance Scheme is an insurance arrangement
between the two....
• Where, the employer purchases an insurance policy for the
employee.
• This arrangement is based on the principle that the employer has an
insurable interest in his/her employees.
• The interesting fact is that both the employee and the employer is
benefited through this arrangement.

3. Qualitative vs. Quantitative Content Analysis
Area of Research - First, the research areas from which they developed
are different. Quantitative content analysis is used widely in mass
communication as a way to count manifest textual elements, an aspect of this
method that is often criticized for missing syntactical and semantic information
embedded in the text. By contrast, qualitative content analysis was developed
primarily in anthropology, qualitative sociology, and psychology, in order to
explore the meanings underlying physical messages.
Inductive vs. Deductive - Second, quantitative content analysis is
deductive, intended to test hypotheses or address questions generated from
theories or previous empirical research. By contrast, qualitative content
analysis is mainly inductive, grounding the examination of topics and themes,
as well as the inferences drawn from them, in the data. In some cases,
qualitative content analysis attempts to generate theory.
Sampling Technique - Third, the data sampling techniques required by
the two approaches are different. Quantitative content analysis requires that
the data are selected using random sampling or other probabilistic approaches,
so as to ensure the validity of statistical inference. By contrast, samples for
qualitative content analysis usually consist of purposively selected texts which
can inform the research questions being investigated.
Outcomes - Fourth, the products of the two approaches are different. The
quantitative approach produces numbers that can be manipulated with various

4. Content
Context
Users
Content Analysis – What?
Text
(Any Occurrence of
communicative
Language)
Words
Images
Video
Features
Physical Items
Signage etc.
It is use to
systematically
summarize written,
spoken, or visual
communication in
a quantitative way.,
It’s About Patterns
and Relationships
Texts can be defined as books, book chapters,
essays, historical-documents, headlines-articles,
conversations, interviews, discussions, speeches
Context can
defined as: “The
circumstances that
form the setting
for an event,
statement, or idea,
and in terms of
which it can be
fully understood
• Managers
• Organization
• Competitors
• Customer
• Employees
• Share Holders
• Suppliers
• Other
Stakeholders

5. Six Questions - Addressed in Content Analysis
Data
Which data
are analyzed?
(do not carry any
specific
meaning)
Six
Questions
Context
What is the
context
relative to
which data are
analyzed?
Information
How are they
defined?
(Carry specific
and logical
Meaning)
Population
What is the
population
from which the
data drawn?
Target
What is the
target of the
inferences?
Boundaries
What are the
boundaries of
the analysis?

6. Content Analysis - Glossary
Understanding Participant’s View: Transcribed interview texts and read &
re-read to get a sense of whole, i.e., to understanding of participant’s View.
Meaning Units: Start dividing up the text into smaller parts, namely, into
meaning units. meaning unit is also refereed to as 'unit of analysis'
Condensation: Condensation is a process of shortening the text. Condenses
these meaning units further, ensure that the core meaning is still retained.
Coding: Label/name condensed meaning units by formulating codes in a way
that most exactly describes what this particular condensed meaning unit is about.
Theme: Themes are expressing data on an interpretative (latent) as it is
expressing an underlying meaning. It is intended to communicate both an
intellectual-emotional level. poetic and metaphoric language to express meaning
Categorization: Grouping together those words with similar meaning or
connotation and the codes that are related to each other through content/context.

7. Manifestation vs. Latent (Abstraction)
A
b
s
t
r
a
c
t
i
o
n
Higher Level
Reflects the
interpreted, latent
meaning of the text
Lower Level
Close to the text
and manifest
content
Theme
Category
Code
Condensed
Meaning
Unit
Meaning
Unit
Price doesn’t matter, quality of product
matters
Product Quality
Dissatisfaction
Unhappy with the use of product
Unfortunately, I haven’t good experience
for the use of the product ‘A’. I think,
there is some better options.

8. Types of Content Analysis
• Determines the existence and
frequency of concepts in a text. i.e.
quantifying and counting its presence.
• The main goal is to examine the
occurrence of selected terms in the
data. Terms may be explicit or implicit.
• Develops the conceptual analysis
further by examining and exploring the
relationships among concepts in a text
• Individual concepts are viewed as
having no inherent meaning and rather
the meaning is a product of the
relationships among concepts.

9. Types of Content Analysis
Conceptual content Analysis Relational Content Analysis
Decide the level of analysis
Decide how many concepts to code for
Decide whether to code for existence or
frequency of a concept
Decide on how you will distinguish
among concepts
Develop rules for coding your texts
Decide what to do with irrelevant information
Code the text
Analyze your results
Decide the level of analysis
Reduce the text to categories and code for
words or patterns
Explore the relationship between concepts
Strength – Sign - Direction
Code the relationships
Perform statistical analyses
Map out representations

10. Three Approaches - Content Analysis
Coding categories are derived
directly from text data. Generally
used with a study design whose
aim is to describe a phenomenon
and research literature on a
phenomenon is limited.
Starts with theory or relevant
research findings as guidance
for initial codes. The goal of a
directed approach is to validate
or extend conceptually a
theoretical framework or theory.
Involves counting and comparisons,
usually of keywords or content, followed
by the interpretation of the underlying
context. Study starts with keywords and
center on how initial codes are
developed
Conventional Directed
Summative
Coding
schemes,
Origins of
codes, and
Validity.

11. Major Differences
Type of Content
Analysis
Study Starts
With
Timing of Defining
Codes or Keywords
Source of Codes or
Keywords
Conventional
Observation
(Inductive)
Codes are defined
during data analysis
Codes are derived
from data
Directed
Theory
(Deductive)
Codes are defined
before and during data
analysis
Codes are derived
from theory or
relevant research
findings
Summative
Keywords
(Mixed)
Keywords are identified
before and during data
analysis
Keywords are derived
from interest of
researchers or review
of literature

12. Content Analysis - Why?
• Researchers use content analysis to find out about the purposes, messages,
and effects of communication content to provide knowledge and
understanding of the phenomenon under study
• Content analysis explores human experience and they are expediently
studied through analyzing textual data e.g., collected in individual interviews,
focus groups, documents, or documented participant observation.
• The objective in qualitative content analysis is to systematically transform a
large amount of text into a highly organized and concise summary of key
results and examining trends and patterns in documents
• They can also make inferences about the producers and audience of the
texts they analyze.
• Content analysis can be used to quantify the occurrence of certain words,
phrases, subjects or concepts in a set of historical or contemporary texts.

13. • Content Analysis can be Applied to….
Examine any piece of writing or occurrence of recorded communication;
thus it used in a dizzying array of fields such as
Marketing and media studies,
Ethnography and Cultural studies,
Sociology , Political science, Psychology and Cognitive science, and
many other fields of inquiry.
• Uses of content analysis:
• Detect the existence of ideas, Concepts and truth hidden in the texts.
• Identify the intentions, focus or communication trends of an individual,
group or institution
• Describe attitudinal and behavioural responses to communications
• Determine psychological or emotional state of persons or groups
Uses of content Analysis

14. Reliability
Accuracy
Closeness
of
categories
Consistently re-code the same
data in the same way over a
period of time
Tendency for group of coders to
classify categories in the same
way.
Extent to which classification of
text corresponds to a norm or
standard statistically
Concept category can be
broadened to include synonyms
or implicit variables.
Do conclusions correctly follow
the data? Are results
explainable by other
phenomena?
Generalizability of the results to
a theory
Stability
Reproducibility
Conclusions
Generalizability
Validity

15. Advantages of content Analysis
Disadvantage
Advantage
Unobtrusive
Data Collection
Highly Flexible
Communication & social interaction can be analyzed
without direct involvement of participants, so
presence of researcher doesn’t influence results.
You can conduct content analysis at any time, in
any location, and at low cost – all you need is
access to the appropriate sources.
Transparent
and Replicable
content analysis follows a systematic procedure that
can easily be replicated by other researchers,
yielding results with high reliability
Reductive
Time Intensive
Focusing on words or phrases in isolation can
sometimes be overly reductive, disregarding
context, nuance, and ambiguous meanings.
Manually coding large volumes of text is extremely
time-consuming, and it can be difficult to automate
effectively.
Subjective
Content analysis involves some level of subjective
interpretation, which can affect the reliability and
validity of the results and conclusions.

16. Thank You

17. General steps - Conceptual Content Analysis
1. Decide the level of analysis: word, word sense, phrase, sentence, themes
2. Decide how many concepts to code for: develop pre-defined or interactive set of
categories or concepts. Decide either:
A. To allow flexibility to add categories through the coding process, or
B. To stick with the pre-defined set of categories.
Option A allows for the introduction and analysis of new and important material that
could have significant implications to one’s research question.
Option B allows the researcher to stay focused and examine the data for specific
concepts.
3. Decide whether to code for existence or frequency of a concept. The decision
changes the coding process.
When coding for the existence of a concept, count a concept only once if it appeared
at least once in the data and no matter how many times it appeared.
When coding for the frequency of a concept, the researcher would count the number
of times a concept appears in a text.

18. General steps - Conceptual Content Analysis
4. Decide on how you will distinguish among concepts: Should text be
coded exactly as they appear or coded as the same when they appear in
different forms? The rules could make all of these word segments fall into
the same category, or perhaps the rules can be formulated so that the
researcher can distinguish these word segments into separate codes.
5. Develop rules for coding your texts. After decisions of steps 1-4 are
complete, a researcher can begin developing rules for translation of text into
codes. This will keep the coding process organized and consistent. Validity
of the coding process is ensured when the researcher is consistent and
coherent in their codes, meaning that they follow their translation rules. In
content analysis, obeying by the translation rules is equivalent to validity.
6. Decide what to do with irrelevant information: should this be ignored
(e.g. common English words like “the” and “and”), or used to reexamine the
coding scheme in the case that it would add to the outcome of coding?

19. General steps - Conceptual Content Analysis
7. Code the text: This can be done by hand or by using software.
By using software, researchers can input categories and have coding done
automatically, quickly and efficiently, by the software program.
When coding is done by hand, a researcher can recognize error far more
easily (e.g. typos, misspelling). If using computer coding, text could be
cleaned of errors to include all available data.
This decision of hand vs. computer coding is most relevant for implicit
information where category preparation is essential for accurate coding.
8. Analyze your results: Draw conclusions and generalizations where
possible.
Determine what to do with irrelevant, unwanted or unused text: reexamine,
ignore, or reassess the coding scheme.
Interpret results carefully as conceptual content analysis can only quantify
the information. Typically, general trends and patterns can be identified

20. Reliability: Because of the human nature of researchers, coding errors can never be
eliminated but only minimized.
Generally, 80% is an acceptable margin for reliability. Three criteria comprise the reliability
of a content analysis:
1. Stability: the tendency for coders to consistently re-code the same data in the same
way over a period of time.
2. Reproducibility: tendency for a group of coders to classify categories membership in the
same way.
3. Accuracy: extent to which the classification of text corresponds to a standard or norm
statistically.
Reliability and Validity
Validity: Three criteria comprise the validity of a content analysis:
1. Closeness of categories: this can be achieved by utilizing multiple classifiers to arrive at
an agreed upon definition of each specific category. Using multiple classifiers, a concept
category that may be an explicit variable can be broadened to include synonyms or
implicit variables.
2. Conclusions: What level of implication is allowable? Do conclusions correctly follow the
data? Are results explainable by other phenomena? This becomes especially problematic
when using computer software for analysis and distinguishing between synonyms. For
example, the word “mine,” variously denotes a personal pronoun, an explosive device,
and a deep hole in the ground from which ore is extracted. Software can obtain an
accurate count of that word’s occurrence and frequency, but not be able to produce an
accurate accounting of the meaning inherent in each particular usage. This problem could

21. How to Conduct Content Analysis
If you want to use content analysis in your research, you need to start with a
clear, direct research question.
Example research question for content analysis
Is there a difference in how the US media represents male and female
politicians in terms of trustworthiness? Next, you follow these five steps.
1. Select the content you will analyze
Based on your research question, choose the texts that you will analyze. You
need to decide: The medium (e.g. newspapers, speeches or websites) and
genre (e.g. opinion pieces, political campaign speeches, or marketing copy)
The criteria for inclusion (e.g. newspaper articles that mention a particular
event, speeches by a certain politician, or websites selling a specific type of
product)
The parameters in terms of date range, location, etc. If there are only a small
amount of texts that meet your criteria, you might analyze all of them. If there is
a large volume of texts, you can select a sample.
To research media representations of male and female politicians, you decide
to analyze news articles and opinion pieces in print newspapers between
2017–2019. Because this is a very large volume of content, you choose three

22. Unobtrusive data collection
You can analyze communication and social interaction without the direct
involvement of participants, so your presence as a researcher doesn’t influence
the results.
Transparent and replicable
When done well, content analysis follows a systematic procedure that can easily
be replicated by other researchers, yielding results with high reliability.
Highly flexible
You can conduct content analysis at any time, in any location, and at low cost –
all you need is access to the appropriate sources.
Disadvantages of content analysis
Reductive
Focusing on words or phrases in isolation can sometimes be overly reductive,
disregarding context, nuance, and ambiguous meanings.
Subjective
Content analysis almost always involves some level of subjective interpretation,
which can affect the reliability and validity of the results and conclusions.
Time intensive
Manually coding large volumes of text is extremely time-consuming, and it can
Advantages of content Analysis