Cite as: Carroll, CE. (2014, May) " Stakeholder inclusiveness as argument pro homine in CSR reports." International Communication Association, Seattle, WA.
Stakeholder inclusiveness as argument pro homine in CSR reports
1.
2. STAKEHOLDER ENGAGEMENT
Inherent Part of CSR
• Characteristic of corporate social
responsibility
• To what extent can CSR exist
authentically, without stakeholder
engagement?
Instrumental part of
transparency and disclosure
• A means to ensure that transparency exists or
that transparency improves
• Organizations report on their CSR strengths and
weaknesses in CSR annual reports.
• Stakeholder engagement is one area where
companies are expected to disclose their
progress.
3. STAKEHOLDER INCLUSIVENESS
• A firm “should identify its stakeholders and explain in the report how it has responded to
their reasonable expectations and interests” (Global Reporting Initiative, 2011, p. 10).
4. THE FUNCTION OF TRANSPARENCYTo allow those who do not have direct experience with a firm
to see or inspect for themselves what is going on inside the firm
On issues, actions, and decision-making procedures
about which they seek first-hand information
to make informed decisions and judgments
CSR Reports are designed to make companies more transparent.
Carroll, C. E., & Einwiller, S. A. (2014). Disclosure alignment and transparency signaling in CSR reporting. In
R. P. Hart (Ed.), Communication and Language Analysis in the Corporate World (pp. 249-270). Hershey, PA:
IGI-Global.
5. IN CSR REPORTS…
A RESPONSE TO SOCIETY’S DEMANDS…
Companies seek to reveal
themselves as:
•Transparent, with little or nothing to
hide;
•Rule-followers, meeting the
demands of their stakeholders,
We suggest they are engaging
in-
•Transparency signaling refers to
organizational efforts to demonstrate
transparency
•Disclosure alignment: conforming
to CSR reporting guidelines and
expectations
Carroll, C. E., & Einwiller, S. A. (2014). Disclosure alignment and transparency signaling in CSR reporting. In
R. P. Hart (Ed.), Communication and Language Analysis in the Corporate World (pp. 249-270). Hershey, PA:
IGI-Global.
6. TRANSPARENCY SIGNALING
Positive (+) Transparency
Signals
• Signals whose presence suggests transparency.
The more positive transparency signals, the more the
organization can claim transparency (and the more
audiences will/should perceive transparency).
Negative (-) Transparency
Signals
• Signals whose presence suggests a lack of
transparency.
• Negative transparency signals are minimized,
moderated, or absent for one claim
transparency.
The less negative transparency signals, the more the
organization can claim transparency (and the less
audiences will/should perceive transparency).
Carroll, C. E., & Einwiller, S. A. (2014). Disclosure alignment and transparency signaling in CSR reporting. In
R. P. Hart (Ed.), Communication and Language Analysis in the Corporate World (pp. 249-270). Hershey, PA:
IGI-Global.
7. TRANSPARENCY SIGNALING
Positive (+)
Transparency Signals
•Balance
•Individual ownership (taking ownership of one’s message)
•Guidance and direction (specify who, what, when, where)
•Accuracy
•Concreteness
• Timeliness
• Stakeholder Inclusiveness
Negative (-)
Transparency Signals
•Anti-balance
•Ambivalence
•Assortment
•Attachment
•Adornment
I Suggest that…
Has two dimensions
“Big Acts”of Transparency The 5 As to Avoid
Stakeholder
Inclusiveness is a
“Positive” Transparency
Signal
Carroll, C. E., & Einwiller, S. A. (2014). Disclosure alignment and transparency signaling in CSR reporting. In
R. P. Hart (Ed.), Communication and Language Analysis in the Corporate World (pp. 249-270). Hershey, PA:
IGI-Global.
8. DISCLOSURE ALIGNMENT
CSR Report Contents
1. Materiality
2. Stakeholder Inclusiveness
3. 6 Topics of CSR
CSR Report Quality
1. Timeliness
2. Balance
3. Clarity
4. Accuracy
5. Reliability
We Suggest…
Carroll, C. E., & Einwiller, S. A. (2014). Disclosure alignment and transparency signaling in CSR reporting. In
R. P. Hart (Ed.), Communication and Language Analysis in the Corporate World (pp. 249-270). Hershey, PA:
IGI-Global.
Has two dimensions
Stakeholder Inclusiveness
is an indicator of Disclosure
Alignment with the Global
Reporting Initiative’s CSR
Report Contents
9. 3 PERSPECTIVES ON TRANSPARENCY &
DISCLOSURE ALIGNMENTWhere do transparency and disclosure alignment exist?
Who gets to say?
Transparency as a claim
Transparency as meeting defined criteria
Transparency as a perception, opinion,
judgment, or evaluation
10. WHAT IS THE “RIGHT” AMOUNT OF TRANSPARENCY
SIGNALS AND DISCLOSURE ALIGNMENT?
Goldilocks’ “Not too hot, not too cold. Just right.”
Medium
Excessive. Information overload. “Jamming”/overloading the system. Saying so much that
you say nothing at all.
High
Insufficient. Lacking in detail.
LowA “high” amount of
stakeholder
inclusiveness offers the
potential for “Argument
Pro Homine.”
11. HOW DO WE “KNOW” WHAT THE RIGHT AMOUNT IS?
• One organization’s (communicative) behavior
over time
• A set of organizations’ (communicative)
behavior at any one time
• A set of organizations’ (communicative)
behavior over time
“NO!”
Expectations established based upon comparisons Do we have such points of comparison?
A NORMATIVE APPROACH
13. Truth
Lies Truthlike
What makes truthiness so much more dangerous
than lies is that for one to lie, one must know the
truth (at least respect it enough to know what the
truth is).
Truthiness has no regard or respect for the truth at
all.
“how do we detect when an organization is being
“truthy”?
14. ARGUMENT PRO HOMINE
• To argue pro homine is to argue for the person as evidence rather than presenting the argument
or evidence directly.
• An argument pro homine is the inverse of the ad hominem argument.
• It is concerned by the frequent casual insertion of any CAMPUS into organizational discourse
without concern for context, relevance, or materiality.
• Is it name dropping?
15. ARGUMENT PRO HOMINE
• Predicate 1: Firm A asserts CSR claim 1.
• Predicate 2: CAMPUS (Constituent, Audience, Market, Public, User, Stakeholder) B—which has
been predetermined as credible, competent, legitimate or reputable—co-occurs with Claim 1.
• Therefore, Proposition 1 is true.
16. ARGUMENT PRO HOMINE
• Pro homine arguments embody the halo effect, a cognitive bias in which the perception of one
trait is influenced by the perception of an unrelated trait.
• An example of the halo effect is treating an attractive person as more intelligent or more honest
than an unattractive person.
17. EXAMPLE FROM THE NYT…
“Dozens of prominent Republicans [emphasis
added] signed a soon-to-be-filed amicus brief…
arguing for a constitutional right to same-sex
marriage."
“Legal analysts said the brief had the potential
to sway conservative justices as much for the
prominent names attached to it as for its legal
arguments.”
Stohlberg, S. G. (2013). Republicans Sign Brief in Support of Gay Marriage, The New York Times, p. A1. Retrieved
from http://www.nytimes.com/2013/02/26/us/politics/prominent-republicans-sign-brief-in-support-of-gay-
marriage.html?_r=0
Demonstrating the persuasive
power of argument pro homine,
18. INSTITUTIONAL RHETORIC
• Language matters.
• Language signals institutional values.
• Language patterns are of special importance
Hart, R. P. (2014). Communication and Language Analysis in the Corporate World. Hershey, PA: IGI-Global.
19.
20. SAMPLE
Firms
• U.S. Firms listed in Global Forbes
2000
• 36 firms
• 24 publicly subscribing to GRI
• 22 not publicly subscribing
Texts
• CSR Annual Reports from 2011
• PDFs downloaded from corporate
websites
• Corporate Register.com
21. DICTION 6.0
Background
• 35 theoretically-derived, mutually
exclusive keyword dictionaries
• 10,000 words
• most robust rhetorical understanding of
the text.
• “IF you could only ask 5 questions of a
text, these would be the five.”
Hart, R. P., & Carroll, C. E. (2011). DICTION 6.0. Austin, TX USA: Digitext, Inc.
www.dictionsoftware.ccom
22. KEY ASSUMPTIONS
1. Institutional actors (evenly sophisticated ones like PR professionals and corporate
attorney) rarely monitor their lexical decisions.
2. That they have no ability at all to monitor (all of) their lexical patterns.
3. That they think they have control over such matters
Hart, R. P. (2014). Communication and Language Analysis in the Corporate World. Hershey, PA: IGI-Global.
23. ASSUMPTIONS ABOUT TONE
(1) Families of words have their own distinctive valence but become
mutually implicative when combined;
(2) tone becomes more identifiable when word families are commingled;
(3) tone becomes more forceful when these families are repeatedly
commingled; and
(4) lexical layering explains differences among rhetorical genres—how a
poem can be distinguished from a movie script, for example (Ishizaki &
Kaufer, 2012).
Hart, R. P., Childers, J. P., & Lind, C. J. (2013). Political Tone: How Leaders Talk and Why. Chicago, IL:
University of Chicago Press.
24. TONE IS THE PRODUCT OF…
1)individual word choices that…
2)cumulatively build up…
3)to produce patterned expectations…
4)telling an audience something important…
5)about the author's outlook on things.
Hart, R. P., Childers, J. P., & Lind, C. J. (2013). Political Tone: How Leaders Talk and Why. Chicago, IL:
University of Chicago Press.
25. POLITICS…
It is also a world of poorly understood words,
“Politics is a world of words.
Hart, R. P., Childers, J. P., & Lind, C. J. (2013). Political Tone: How Leaders Talk and Why. Chicago, IL:
University of Chicago Press.
poorly remembered words,
and poorly theorized words.”
26. • People are “gist processors”…taking what they need and leaving the rest.
• People listen for context (yes), but they also listen for lexical weight.
• People do their own “dictionary look ups”
Hart, R. P., Childers, J. P., & Lind, C. J. (2013). Political Tone: How Leaders Talk and Why. Chicago, IL:
University of Chicago Press.
27. DICTION 6.0
Norms Drawn from Hart’s prior
DICTION analyses of over
20,000 texts
• Political speeches
• News coverage
• Advertisements
• Religious sermons
• Scientific reports
• Corporate press releases
• Corporate financial reports
• Public policy speeches
• Social protest movements
Hart, R. P., & Carroll, C. E. (2011). DICTION 6.0. Austin, TX USA: Digitext, Inc.
www.dictionsoftware.com
28. DICTION
CSR Report Content
1. Materiality + Insistence
+ Centrality
2. Stakeholder
inclusiveness
+ Cooperation
+ Collectives
+ Human Interest
– Diversity
Report Quality
1. Balance + Hardship
+ Accomplishment
– Praise
– Satisfaction
2. Timeliness + Present Concern
3. Accuracy + Numerical Terms
4. Clarity – Ambivalence
5. Reliability + Inspiration
DICTION
Positive Transparency Signals
1. Balance + Hardship
+ Accomplishment
2. Timeliness +Present Concern
3. Accuracy +Numerical Terms
4. Individual Ownership +Self–reference
5. Guidance + Familiarity
6. Concreteness + Concreteness
7. Stakeholder + Cooperation
Inclusiveness + Collectives
+ Human Interest
– Diversity
Negative Transparency Signals
1. Anti-balance – Praise
– Satisfaction
2. Ambivalence (Anti-clarity) – Ambivalence
3. Assortment – Variety
4. Attachment – Rapport
5. Adornment – Embellishment
Carroll, C. E., & Einwiller, S. A. (2014). Disclosure alignment and transparency signaling in CSR reporting. In R. P.
Hart (Ed.), Communication and Language Analysis in the Corporate World (pp. 249-270). Hershey, PA: IGI-Global.
29. DICTION NORMS
Hart, R. P., & Carroll, C. E. (2011). DICTION 6.0. Austin, TX USA: Digitext, Inc.
www.dictionsoftware.com
30.
31. STEPS
1. Scored the texts with DICTION,
2.Examined DICTION’s Insistence words
3.Parsed out DICTION’s Insistence words about
CAMPUS (topical density)
4.Scored the measure of CAMPUS
5.Compared against DICTION’s norms
6.Compared each CSR Report against the sample
CAMPUS
Constituents
Audiences
Markets
Publics
Users
Stakeholders
32. AN EXAMPLE OF INSISTENCE
Yak!
Yak!
Yak!
Yak!
Yak!
Mom when you were growing up
33. Mom when you were growing up
AN EXAMPLE OF TOPICAL DENSITY
Clean Your Room!
Wipe off your
feet when you
come in the
house.
Fill the
tank up
with gas!
Why weren’t
you home
before
midnight?
Get a haircut!
34. DICTION’S INSISTENCE MEASURE
AND ITS HISTORICAL NORMS
• Insistence counts repeated words within
concentrated passages (500-word
increments), thereby measuring the degree
to which a text stays on-topic (or changes
topic) over the course of a text
• Captures all words appearing 3 or more
times within a 500 word passage.
Hart, R. P., Childers, J. P., & Lind, C. J. (2013). Political Tone: How Leaders Talk and Why. Chicago, IL:
University of Chicago Press.
35. INSISTENCE
Count of words appearing 3 or more times
X
Sum of words appearing 3 or more times
+ .10
Add scores of the 500 word passages/divided by number of
500-word passages
36. CAMPUS TOPICAL DENSITY MEASURE
Count of the eligible CAMPUSIG-nouns
X
Sum of the eligible CAMPUSIG-nouns
+ .10
Add scores of the 500 word passages/divided by number of
500-word passages
For each firm’s report:
37. 2 HUMAN CODERS, W/1 INDEPENDENT
REVIEWER
• The two coders had to agree that a word was eligible for the CAMPUS topical density measure.
• A tie breaker.
38. COMPARISON OF SCORES
Compared against DICTION’s historical norms for insistence (above,
within, and below the norms)
Scores standardized.
>+1 Z score: above the norm
<1 to >-1 Z scores:“within” the norm
< -1 Z score: “below” the norm
CAMPUS
Constituents
Audiences
Markets
Publics
Users
Stakeholders
Candidate for Argument Pro Homine
Insufficient
Stakeholder Inclusiveness
39.
40. SUMMARY
Descriptives
• 255 unique CAMPUS terms
• Used 3,555 times
GRI vs non-GRI firms
• Firms declaring public support for the GRI’s
reporting principles had slightly more
stakeholder inclusiveness, but the
difference was marginal (p < .10)
41. TOPICAL DENSITY MAPSThe CAMPUS term “employees” had the
largest degree of topical density, followed
by suppliers, and then customers
The CAMPUS terms with least topical
density included girls, elderly, educator,
scientist, policy maker, advocates, farmer
42. DISTRIBUTION OF FIRMS FOR
STAKEHOLDER INCLUSIVENESS TOPICAL
DENSITY
Against DICTION’s historical
norms
• 35 of 36 firms fell within the normative range
for DICTION’s Insistence
• 1 firm fell below the norm.
“Norms” within the sample
• 5 of 36 firms were above the norm (Z score of +1
or higher)
• 25 firms were “within” the norm (Z score
• 6 of 36 firms were below the norm (Z score of -1
or lower)
43. CONCLUSIONS
• Presence of pro homine appears when just considering the sample, but not evident
when compared against DICTION’s historical norms
• Appeared possible within 5 of 36 firms
44. FUTURE RESEARCH
1. Establishment of CSR norms for CAMPUS topical density using larger sample (full Global
Forbes 500, and examined over time.
2. CSR reports compared on a per topic basis (Product, Labor, Society, Human Rights,
Environment, Economic Performance)
3. Comparing within CAMPUS/stakeholder groups (Employees, Customers, Investors,
Community, Partners, Regulators)
Hinweis der Redaktion
Relies on 35 theoretically-derived keyword dictionaries containing over 10,000 words that are mutually exclusive (Hart, 2001). DICTION provides the most robust rhetorical understanding of the text. “IF you could only ask 5 questions of a text, these would be the five.”
Predicated on the contention that texts are embedded within communities of discourse, and thus contain norms.
The norms are drawn from Hart’s prior DICTION analyses of over 20,000 texts drawn from general public discourse, including political speeches, news coverage, advertisements, religious sermons, scientific reports, corporate press releases, corporate financial reports, etc. providing what Hart calls a more precise textual understanding.
Determines the relative importance of each of its variables within each text by comparing the concepts’ calculated scores against a normative range (an upper and lower limit) established by averaging the scores of thousands of texts from widest range of genres over an extended time
Relies on 35 theoretically-derived keyword dictionaries containing over 10,000 words that are mutually exclusive (Hart, 2001). DICTION provides the most robust rhetorical understanding of the text. “IF you could only ask 5 questions of a text, these would be the five.”
Predicated on the contention that texts are embedded within communities of discourse, and thus contain norms.
The norms are drawn from Hart’s prior DICTION analyses of over 20,000 texts drawn from general public discourse, including political speeches, news coverage, advertisements, religious sermons, scientific reports, corporate press releases, corporate financial reports, etc. providing what Hart calls a more precise textual understanding.
Determines the relative importance of each of its variables within each text by comparing the concepts’ calculated scores against a normative range (an upper and lower limit) established by averaging the scores of thousands of texts from widest range of genres over an extended time