Exploring the
Social Discourse of Bioenergy in the Pacific Northwest
Conceptual Framework (3 pages)
Problem
Statement – Social Discourse of Bioenergy
Literature
Review
Proposal for study
Problem
Statement – Social Discourse of Bioenergy
"It
is hard to know how narratives and interpretative policy inquiry can be
converted into real policy guidance in real time, in an environment of real
politics, against the prospect of subsequent evaluation" Lawler 1996 from
Durning 1999- post positivism
The purpose of this research is to assess the feasibility
and potential social impacts of hybrid
poplar biofuels on communities located in the Pacific Northwest United
States. The research team’s principal investigator has instructed our team to
assist in the development of a social marketing plan to engage the public as
part of the first step in Social Impact Assessment. This regional level social
marketing plan will be developed through a collaborative mixed methods approach
utilizing interviews, focus groups, surveys, Q methodology and a thematic
analysis of news articles. I will explore stakeholder perceptions of biofuels
in the Pacific Northwest using Q methodology with stakeholders from Montana,
Idaho, Oregon, Washington, and Northern California following the practices
developed by Brown (1980).
·
What
is a social discourse?
·
Why
is social discourse important?
·
Why
is the media important?
·
Why
is feasibility important?
·
Why
is the Q study important?
·
How
does this help with social acceptance?
Theory –
Look at
Habermas’s Communicative Action Theory
Purposeful
activity in Communication
Consider the
Media à Behavior + Public Opinion
·
What
can policy decision makers do when media influences behavior in certain ways?
Theory –
Look at Cox’s
Environmental Communication in the public sphere
Symbolic Action
in communication: mediates and informs perception of biofuels
Look at the
public sphere as a discursive space
Look at the
Media Coverage of the environment in chapter 3
Theory –
Agenda setting theory - Max Macombs
Research
Problem
As is the case
with any natural resource-based industry, the biofuels industry has potential
for environmental and human impacts.
Human impacts, also known as social impacts include any impact, not just
economic impacts to an given population. This includes: changes in culture –
values, beliefs and norms, how people live their daily lives, changes to the
character of the community, the political power and institutional arrangements
in the community, changes in the health and psychological wellbeing of the community,
impacts on civil liberties, and changes in people’s fears and aspirations
(Becker and Vanclay 2003; Burdge 2004).
The biofuels
industry is complicated to assess because it has undergone many changes
recently and is still in the process of transforming – different feedstock
options will likely impact people differently. In the US and even more so
internationally, there has been substantial social backlash regarding biofuels
production because of rising food prices, indirect land use change, uncertainty
associated with genetic modification, pollution and other potential health
risks (Dodge 2010; Fargione et al. 2010; Kleiner 2008). Recent studies of social acceptability and
the social impacts of biofuels in the United States are limited to surveys at
the national level, or the eastern US where most of the development has taken
place (Delshad et al. 2010). There are few in-depth studies characterizing the
level of knowledge people have, exploring people’s understanding of the
differences between energy options, and characterizing how different
stakeholders perceive biofuels. As such, in the Pacific Northwest it is
difficult to predict how these emerging industries and technologies will be
received and how they will ultimately impact communities.
Background, Context and
Justification (2.5)
As America
progresses through the 21st century the need for sustainable and renewable
forms of energy and materials to fuel the economy and sustain the American
people is becoming increasingly important.
The arguments for moving away from traditional fossil fuel sources are
numerous including: improving national security, preventing environmental
degradation, mitigating climate change, and revitalizing the economy (Akella et al. 2009; Mason et al. 2009). One solution
is developing renewable energy sources such as bioenergy, geothermal, solar and
wind power and actively transitioning from a fossil fuel-based economy and
infrastructure to a renewable energy-based infrastructure and economy (Akella
et al. 2009). Among these potentials,
the development of biofuels has received some of the most attention in the
United States and was initially widely touted as a panacea for America’s “oil
addition.” The first attempts at developing the biofuels industry in the US on
a large scale focused on producing ethanol from corn crops. These biofuels are
known as first generation biofuels. Though various forms of feedstock are
available for conversion into biofuels (algae, switch grass, poplar trees, bio
waste products, forest residuals etc.) corn ethanol was heavily subsidized and
supported initially because there was already existing infrastructure in place
to grow the large quantities of corn needed to produce ethanol at a commercial
scale. However, the scientific
community, environmental community and many others now criticize first
generation biofuels citing a number of factors which reduce their
effectiveness. First generation
biofuels
purportedly require disproportionately large quantities of water, are not cost
effective when the production costs and subsidies are accounted for, and are
grown on land used for food production so they directly and indirectly effect
the available food supply and negatively impact food prices worldwide (Fargione et al. 2010; Naik et al. 2010). As researchers began to recognize the
weaknesses of first generation biofuels, the need for better biofuels emerged.
The new second generation biofuels are primarily produced from cellulosic
sources such as switch grass or poplar trees, and are grown on marginal lands
where food production is minimally impacted (Djomo et al. 2011;
Mason et al. 2009). Cellulosic ethanol from lignin sources such as poplar has
many benefits including: improved forest health, rural community
revitalization, fire prevention, and climate change mitigation (Mason et al.
2009; O’Laughlin 2010). Though
it is unclear at this point if cellulosic ethanol produced from hybrid poplar
plantations will offer a viable long term alternative to fossil fuels, it is
clear that advanced biofuels has potential to play a major role in the
renewable energy portfolio for the country, given that it is economically
viable, environmentally sound and socially acceptable. It is the last point,
the social impact and social acceptability of second generation biofuels that I
consider in this study.
Purpose and Specific Objectives
(1/2 page)
The purpose of this study is to explore
the social discourse of bioenergy in the Pacific Northwest with the specific
goal of unpacking the dynamic social construction of hybrid poplar biofuels. I
intend to meet this goal through the following objectives:
1.
Identify stakeholders in the Pacific
Northwest who may influence the development of hybrid poplar biofuels and
explore the diagnostic framing of biofuels considering stakeholder perceptions
of and attitudes toward biofuels, and illuminate the areas of consensus and
conflict among actors.
2.
Explore the prognostic framing of
biofuels by considering the full range of proposed solutions and management suggestions
proposed by stakeholders and characterize priority areas perceived as problems.
3.
Conduct a computer assisted historical
content analysis of news articles dating from 1999 to the present to examine
how stakeholders’ beliefs, attitudes, perceptions and underlying values toward
biofuels has evolved over time; and compare regional and national trends
4. Conduct
a computer assisted rapid issue tracking content analysis of current news
articles, social media and new media to examine stakeholder beliefs, attitudes,
perceptions and underlying values toward biofuels; and compare social and new
media to traditional news article coverage.
Approach
1.
Objective
I: Identify stakeholders in the Pacific Northwest who may be impacted by or are
influential in the development of hybrid poplar biofuels and explore the diagnostic
framing of biofuels considering stakeholder perceptions of and attitudes toward
biofuels, and illuminate the areas of consensus and conflict among actors. (1
-2 pages)
·
Favorable
Concourse
·
Unfavorable
Concourse
Q Methodology
As explained in the introduction, I will
be employing Q methodology to assess the possible perceptions of stakeholders
toward biofuels in the Pacific Northwest. The Q methodology approach I use is
described fully in Brown (1980). The process consists of 5 distinct steps. The
first step is the development of the concourse of statements which is a
sampling of the range of statements that exist describing a given phenomenon.
The second step involves developing a Q sample, which is a selection of
distinct statements that maximize within group variability for each perception
expressed. The next step involves selecting the P-set, or the participants who
will conduct the sort. The fourth step
is conducting the Q sort, where participants physically sort through a deck of
cards with statements printed on them. The last step is analysis.
Concourse of Statements
There are several ways to develop the
concourse of statement for biofuels including:
collecting statements from public meetings, searching news articles or
conducting interviews. I will define the concourse for biofuels by conducting a
thematic analysis of online news articles and news forums using the key search
terms biofuel(s), biomass, renewable, and bioenergy. These key words were
chosen because of a prior knowledge that participants may not understand the
distinction between each class of energy.
I will search for local, regional and national news articles and forums
to collect statements. Once saturation
is reached, the point where the same ideas are repeated, I will conclude my
search. I will refine the concourse by removing redundant statements and
removing statements that were not frequently expressed in the concourse; which
indicates the ideas were not considered as important.
Selecting the Q Sample
The final Q sample will be selected by
maximizing within category variability for each theme. Salient themes will be selected based on the
best articulated pro, neutral and against statements which capture the
diversity of values expressed in each category.
1. Selecting
the P-set
The P-set is composed of four to five
stakeholders for each perception found in a given theme. This sample size is
sufficient because we are trying to understand the substance of subjectivity in
people’s perceptions rather than trying to make claims about general
perceptions themselves. Including more participants generally does not change
the results of the Q study unless they have extremely outlying viewpoints. I
will select stakeholder groups by looking at references in the news articles
collected during the thematic analysis. In order to ensure stakeholders do
indeed identify themselves with a given stakeholder group, participants will be
asked to indicate their affiliations. Purposeful, snowball sampling will then
be used to identify relevant participants across the region (Denzin and Lincoln
1998). The initial key informants for the snowball sample will be found by
looking at the thematic analysis of news articles, as well as consulting the
list of project collaborators found in the grant proposal. Participants will be selected for the study
if they are individuals who may be impacted by the development of biofuels in
the Pacific Northwest, and also, if they might have influence on the
development of biofuels.
The
P-set in Q methodology is the set of people, or stakeholders in this case, who
will be participating in the Q study. Because this study focuses on policy
development and recommendations, the stakeholders for this study will be
selected based on the criteria that they are knowledgeable about the subject,
have well-formed opinions (which is a general requirement for a successful Q
sort) and are in a position to influence policy or the development of biofuels
in the Pacific Northwest (Addams et al. 2001; Webler et al. 2009). In addition,
the P-set will be designed to maximize the range of perceptions and attitudes
existing toward the concourse on biofuels. As such, the sampling approach for a
P-set is generally purposeful rather than random (Webler et al. 2009). I will
employ a combination of approaches including snowball sampling, seeking expert
opinion and consulting references sourced from regionally relevant news
articles I compiled from the thematic analysis of news articles when I
developed the concourse of statements (snowball sampling reference). Practically
speaking, this entails searching for the CEOs, government officials and leaders
of companies and organizations that are relevant to the development of biofuels
in the Pacific Northwest.
The
number of participants comprising a P-set does not need to be extensive as is
the case in R methodology because the purpose of Q methodology is only to
include enough people to establish the existence of a particular perception,
rather than determining the percentage of representation present in a given
population (Brown 1980). Therefore, the selection of the number of participants
for Q methodology commonly follows a cell structure design, guided by Fisher’s
(1949) principles of experimental design in which the number of participants is
dependent on the number of factors to be explored. The P-structure for this
study will be structured based on a priori theoretical considerations rooted in
environmental policy conventions, as well as inductive considerations emerging
from the thematic analysis of news articles (Webler et al. 2009).
Table 1.
P-Set Structure for each biofuels study
Main Effectsab
|
Levels
|
N
|
A. Stakeholder
Group
|
(a) Industry
(b) Government
(c)
Academia
(d) Environmental
(e) Community
|
5
|
B. State
|
(f) Washington
(g) Oregon
(h) Idaho
(i) Northern California
(j) Montana
|
5
|
C.
|
(k) Diversity 1
(l) Diversity 2
|
2
|
aAB = (5) * (5) = 25 combinations
bABC = (5) * (5) *(2) = 50 combinations
So,
you can either consider the number of factors you would expect to find and go
from the convention of the 3:1 ratio as explained in Webler et al. 2009 or
follow Brown 1980 and consider all of the possible combinations of main
effects. The trick is striking the balance between the two. This leaves us with 25 Q sorts to a possible
(50/3=) 18 Q sorts per each Q study if I choose to keep roughly 55 statements
(observations) in each study. In order to build in redundancy and to ensure the
diversity of different possible perceptions are represented in the sample I
propose to overshoot this target substantially. So, I propose to consider the
25 person p-set over the 18, and then to target at least two people per
combination of factors bringing the new total to 50, and then to increase the
sample to account for the number of incomplete of incompliant volunteers. So, to achieve a p-sample of 50 people we
would need at least 65 people to agree to complete the 4 Q sorts.
Conducting the Q sort
Once an appropriate venue has been
selected, participants will partake, in person, in the q sort. Participants are “forced,” due to lack of
alternatives, to position their views within a normal distribution where
extreme agreement or disagreement with topics can only occur infrequently, and
more moderate perceptions associated with a topic are allowed to occur more
frequently. Forced choice distribution helps the participant understand how
they feel about a topic by forcing them to decide. This is one of the main
advantages of Q methodology over or methods; participants are often surprised
at the outcome, and experience learning how they really feel about a topic as a
result of participating.[ML1]
Analysis and Data Requirements
The resulting Q sorts are analyzed using
a software called PQ software. This software performs a specialized factor
analysis, similar to a principle component analysis, on the q sort output.
Factor analysis is used here to explore within case variability rather than
making across case generalizations. Therefore, the issue of data validity or
statistical significance is not applicable; in exploring the differences or
similarities of people’s subjective opinions, there is no “right” or “wrong”
opinion to be compared against as some measure of “truth” or accuracy.
Stephen Brown
explained it best in his book on political subjectivity, “…all that is required
are enough subjects to establish the existence of a factor for the purposes of
comparing one factor with another. What proportions of the population belongs
in one factor rather than another is a wholly different matter and one about
which Q technique as such is not concerned,” (Brown 1980).
2.
Objective
II: Explore the prognostic framing of biofuels by considering the full range of
proposed solutions and management suggestions proposed by stakeholders and
characterize priority areas perceived as problems. (1
-2 pages)
·
Solutions
Concourse
·
Problems
Concourse
Verifying frames with people who have defining sorts…
3. Objective III: Conduct a computer
assisted historical content analysis of news articles dating from 1999 to the
present to examine how stakeholders’ beliefs, attitudes, perceptions and
underlying values toward biofuels has evolved over time; and compare regional
and national trends. (1 -2 pages)
Search Terms:
Bioenergy,
biofuels, biogas, biochar, green fuel, renewable fuel, energy wood
Historical Content Analysis of
News Articles
Theory and Rationale (Neuendorf 2003)
·
What
content and why?
o
Traditional
News Media Sources Including: radio and TV transcripts, digitized local print,
online news sources, straight news stories, editorials, op eds, letters, and public media records
·
Are
there certain theories or perspectives that indicate this particular message
content is important to study?
·
Research
Questions?
·
Hypothesis?
·
Define
Problem (Bengston et al. 2009)
Conceptualizations
·
What
variables will be used in the study?
·
How
are they defined conceptually?
·
What
messages are important? (Bengston et al. 2009)
·
Timing?
(Bengston et al. 2009)
·
Geographic
focus (Bengston et al. 2009)
·
Stakeholders
(Bengston et al. 2009)
·
Data
Sources and Databases (Bengston et al. 2009)
Operationalizations
·
Unit
of data collection
·
How
are the variables measured? High level of measurement, exhaustive and mutually
exclusive?
·
A
priori coding scheme must be created
·
Face
Validity and Content Validity must be assessed
Coding Schemes
·
Creation
of code book and dictionaries
·
Creating
a custom dictionary?
Sampling
·
Is
a census of the content possible? How will you randomly sample? No, n/a
Coding
·
Apply
dictionaries to generate per unit frequencies for each dictionary. Do spot
check validation
Final Reliability
·
No
intercoder reliability or Pearson’s r calculation is needed because coding is
completed with a computer programmed by one person.
Tabulation
·
Look
for establishment of criterion and construct validity over time, can be
tabulated in different ways.
4. Objective IV: Conduct a computer
assisted rapid issue tracking content analysis of current news articles, social
media and new media to examine how stakeholders’ beliefs, attitudes,
perceptions and underlying values toward biofuels; and compare social and new
media to more traditional news article coverage. (1 -2 pages)
Rapid Issue Tracking Content
Analysis with Social Media and New
Media
Theory and Rationale (Neuendorf 2003)
·
What
content and why?
o
Social
Media and New Media including: blogs, wikis, facebook ,twitter, forums,
websites…possibly reddit? and tumblr? Stumbleupon? – need rational for why
selecting some social media sites and not others…
o
Rational
for monitoring selection:
§
Based
on searchability
§
Based
on popularity
·
Are
there certain theories or perspectives that indicate this particular message
content is important to study?
·
Research
Questions?
·
Hypothesis?
·
Define
Problem (Bengston et al. 2009)
o
Emergence
of controversial new technology
o
New
Policy Initiatives
Conceptualizations
·
What
variables will be used in the study?
·
How
are they defined conceptually?
·
What
messages are important? (Bengston et al. 2009)
·
Timing?
(Bengston et al. 2009)
·
Geographic
focus (Bengston et al. 2009)
·
Stakeholders
(Bengston et al. 2009)
·
Data
Sources and Databases (Bengston et al. 2009)
SOCIAL MEDIA
o
Facebook
– Search
o
Twitter
– Advanced Search delivered through Tweety Mail
o
Comments
– Through Black Word?
o
Tumbler
- ?
o
Reddit
- ?
o
Others
- ?
§
Trappit
– no, because I can’t search it without being searched…it is a discovery engine
not a search engine…
NEW MEDIA
o
Blogs
– Google Alerts and links from social
media
o
Wikis
– Google Alerts and links from social
media
o
Websites
– Google Alerts and links from social
media
GOOGLE INSIGHTS
·
Should
I use?
·
Lets
you see frequency of top stories by state for key word searches over time
GOOGLE TRENDS
·
Should
I use?
·
Lets
you see relative frequency of search terms
·
May
be useful for rational behind selection of search terms
Operationalizations
·
Unit
of data collection
·
How
are the variables measured? High level of measurement, exhaustive and mutually
exclusive?
·
A
priori coding scheme must be created
·
Face
Validity and Content Validity must be assessed
Coding Schemes
·
Creation
of code book and dictionaries
·
Creating
a custom dictionary?
Sampling
·
Is
a census of the content possible? How will you randomly sample? No, n/a
Coding
·
Apply
dictionaries to generate per unit frequencies for each dictionary. Do spot
check validation
Final Reliability
·
No
intercoder reliability or Pearson’s r calculation is needed because coding is
completed with a computer programmed by one person.
Tabulation
·
Look
for establishment of criterion and construct validity over time, can be
tabulated in different ways.
Rapid Issue Tracking Content
Analysis of News Articles
Theory and Rationale (Neuendorf 2003)
·
What
content and why?
o
Traditional
News Media Sources Including: radio and TV transcripts, digitized local print,
online news sources, straight news stories, editorials, op eds, letters, and public media records
·
Are
there certain theories or perspectives that indicate this particular message
content is important to study?
·
Research
Questions?
·
Hypothesis?
·
Define
Problem (Bengston et al. 2009)
Conceptualizations
·
What
variables will be used in the study?
·
How
are they defined conceptually?
·
What
messages are important? (Bengston et al. 2009)
·
Timing?
(Bengston et al. 2009)
·
Geographic
focus (Bengston et al. 2009)
·
Stakeholders
(Bengston et al. 2009)
·
Data
Sources and Databases (Bengston et al. 2009)
Operationalizations
·
Unit
of data collection
·
How
are the variables measured? High level of measurement, exhaustive and mutually
exclusive?
·
A
priori coding scheme must be created
·
Face
Validity and Content Validity must be assessed
Coding Schemes
·
Creation
of code book and dictionaries
·
Creating
a custom dictionary?
Sampling
·
Is
a census of the content possible? How will you randomly sample? No, n/a
Coding
·
Apply
dictionaries to generate per unit frequencies for each dictionary. Do spot
check validation
Final Reliability
·
No
intercoder reliability or Pearson’s r calculation is needed because coding is
completed with a computer programmed by one person.
Tabulation
·
Look
for establishment of criterion and construct validity over time, can be
tabulated in different ways.
Intellectual Merit (1/2 page)
·
Has
anyone done this before?
Application of Research
Results (1/2 page)
Clientele for
study – policy makers in PNW, and Stakeholders
·
How
is it useful?
·
A
majority of the environmental groups we identified have not formed their
platforms or taken positions on the biofuels issue in the Pacific Northwest
yet, so the Q sorts represent an early indication of how these groups may
position themselves in the future.
Tentative Budget (1/2 page)
Tentative Timeline (1/2 page)
I have based this timeline off of
the numbers I anticipate for the stakeholder design in a typical Q study as
outlined by Webler and Tuler . Given that a typical Q study requires between 12
- 36 people for a study, and the fact that I am likely going to propose three Q
studies (Benefits, Solutions and Problems), I will probably require roughly 120
participants for the three Q studies I am proposing. Considering that 5 states
comprise the study area (Oregon, Washington, Idaho, Montana and Northern
California) I anticipate 8 participants per state per each study, which allows
for roughly 2 people per stakeholder group in each state (academia, industry,
government, environmental) for each Q study. Based on the mail response rate
for Kristine’s thesis I anticipate that 2/3rds of the study will be
successfully completed by mail and 1/3 will require in person
administration. I will distribute the Q
sorts by mail by the end May, and this should give me a long enough time period
to judge how many additional in person Q-sorts I may need to conduct. Following
my initial plan this leaves me with 15 in person Q sorts to conduct per each of
the three Q studies over a period of 3-4 months, or roughly 15 in person sorts
per month starting at the end of May, or whenever the IRB processes is
complete.
References
Akella,
A. K., R. P. Saini, and M. P. Sharma. 2009. "Social, economical and
environmental impacts of renewable energy systems". Renewable
Energy. 34 (2): 390-396
Asah,
Stanley T., David N. Bengston, Keith Wendt, and Leif DeVaney. 2012.
"Prognostic Framing of Stakeholders' Subjectivities: A Case of All-Terrain
Vehicle Management on State Public Lands".Environmental
Management. 49 (1): 192-206.
Becker,
H. A., and Frank Vanclay. 2003. The International handbook of social impact
assessment: conceptual and methodological advances. Cheltenham, UK: Edward
Elgar.
Binder, A. R., M. A. Cacciatore, D. A.
Scheufele, B. R. Shaw, and E. A. Corley. 2011. "Measuring risk/benefit
perceptions of emerging technologies and their potential impact on
communication of public opinion toward science". Public Understanding of
Science.
Brown,
Steven R. 1980. Political subjectivity: applications of Q methodology
in political science. New Haven: Yale University Press.
Burdge, R.J. 2004. The Concepts,
Process and Methods of Social Impact Assessment: Rabel J. Burdge and Colleagues.
Middleton, Wisconsin: Social Ecology Press.
Dale,
Virginia H, Rebecca A Efroymson, and Keith L Kline. 2011. “The land use-climate
change-energy nexus.” Landscape Ecology 26 (6) (July): 755-773.
doi:10.1007/s10980-011-9606-2.
Denzin,
Norman K, and Yvonna S Lincoln. 1998. Strategies of qualitative inquiry.
Thousand Oaks, Calif.: Sage Publications.
Djomo,
Sylvestre Njakou, Ouafik El Kasmioui, and Reinhart Ceulemans. 2011. “Energy and
greenhouse gas balance of bioenergy production from poplar and willow: a
review.” Global Change Biology Bioenergy 3 (3) (June): 181-197.
doi:10.1111/j.1757-1707.2010.01073.x.
Dodge,
J. 2010. Biomass delay sought Protest: Crowd gathers again at Olympic Region
Clean Air Agency to oppose projects. The
Olympian: 7 October 2010. http://www.theolympian.com/2010/10/07/1395305/biomass-delay-sought.html
Duncan,
Marvin. 2003. “U.S. Federal Initiatives to Support Biomass Research and
Development.” Journal of Industrial Ecology 7 (3-4): 193-201.
doi:10.1162/108819803323059479.
Fargione, Joseph E., Richard J. Plevin, and Jason
D. Hill. 2010. "The Ecological Impact of Biofuels". Annual Review of Ecology,
Evolution, and Systematics. 41:
351.
Kleiner,
Kurt. 2008. "The backlash against biofuels".Nature Reports Climate
Change. (0801): 9-11.
Mason,
C. Larry, Richard Gustafson, John Calhoun, Bruce Lippke, and Natalia Raffaeli.
2009. Wood to Energy in
Washington: Imperatives, Opportunities, and Obstacles to Progress. Report to the Washington State
Legislature, School of Forestry. College of the Environment. U. of Washington
Naik S.N., Goud V.V., Rout P.K., and Dalai
A.K. 2010. "Production of first and second generation biofuels: A
comprehensive review". Renewable and Sustainable Energy
Reviews. 14 (2): 578-597.
O'Laughlin,
Jay. pages 129-133 in T.B. Jain, R.T. Graham, and J. Sandquist, tech. eds.
(2010) Integrated Management of Carbon Sequestration and Biomass
Utilization Opportunities in a Changing Climate: Proceedings of the
2009 National Silviculture Workshop; 2009 June 15-18; Boise, ID.
Proceedings RMRS-P-61. Fort Collins, CO: U.S. Department of Agriculture, Forest
Service, Rocky Mountain Research Station.
Pickens, Jeffery. Pages 43-76. in Borkowski,
Nancy. 2005. Organizational behavior in health care. Sudbury, Mass:
Jones and Bartlett Publishers.
Appendix I: Tentative Budget
Budget Item
|
Estimated
Cost
|
Q-sort
materials
|
0
|
Honorarium to
participants
|
unknown
|
Travel
|
unknown
|
Q-analysis software
|
0
|
Lexis Nexus
Search Service Fee
|
0
|
Printing,
Mailing and Pre- and Follow-up phone interviews
|
0
|
Appendix II: Tentative Timeline for Q
Studies and Content Analysis Proposal
