Editing Development communication (section)

==== Methods in communication policy analysis ====
Ongkiko and Flor (2006)<ref name="OandF" /> argue that a development communication specialist (DCS), at one time or another, also assumes the role of a communication policy analyst in Communication Policy Analysis 'because of his proactive posture and his preoccupation with purpose' (Flor, 1991). Remember that policy sciences anticipates, and looks forward, thus, substantiates the proactive nature of a DCS. In order to fully act out this role, there is a need for a rudimentary knowledge of methods in policy analysis, particularly those related to development communication.<ref name=":2" /> Among these methods are discussed below:

===== Communication technology assessment (CTA) =====
Communication plays a vital role in project coordination, management, knowledge collection and transfer among different project shareholders (Malone & Crowston, 1994; Espinosa & Carmel, 2003, as cited by Gill, Bunker, & Seltsikas, 2012<ref>{{Cite web
| url = http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1123&context=pacis2012
| title = Evaluating A Communication Technology Assessment Tool (CTAT): A Case of a Cloud Based Communication Tool
|author1=Gill, A. |author2=Bunker, D. |author3=Seltsikas, P.
| date = 2012
| website = aisel.aisnet.org
| access-date = 29 February 2016
}}</ref>). CTA is a qualitative method that seeks to determine the higher and lower order impacts of specific forms of communication technology on the individual and society (Flor, 1991) prior to the adoption of new technology (Ongkiko & Flor, 2006<ref name="OandF" />). The decision to adopt or not depends on the findings of the assessment. CTA is forward-looking and adopts certain value premises on what is socially beneficial or detrimental to society.<ref name=":2" /> Being anticipatory in nature, CTA forecasts, at least on a probabilistic basis, the full spectrum of possible consequences of technological advance, leaving to the political process the actual choice among the alternative policies in the light of the best available knowledge of their likely consequences (Brooks, 1976, as cited by Ely, Zwanenberg, & Stirling, 2010).<ref name=":11">Ely, Adrian, Zwanenberg, Patrick Van, & Stirling, Andrew (2010). ''Technology Assessment: New Model of Technology Assessment for Development.'' Accessed online from http://steps-centre.org/wp-content/uploads/Technology_Assessment.pdf [24 April 2016]</ref> In this case, it should provide an unbiased analysis and information concerning the physical, biological, economic, social, and political effects of [communication] technologies.<ref name=":11" />

===== Cost-Benefit Analysis =====
Introduced by Jules Dupuit in the 1840s, French engineer and economist, the cost benefit analysis is a methodology used in policy analysis as a way of weighing up projects costs and benefits, to determine whether to go ahead with a project.

Beyea (1999),<ref>{{Cite web|url=https://www.enotes.com/homework-help/topic/cost-benefit-analysis-decision-making-public|title=Cost Benefit Analysis: Decision Making in the Public Sector Questions and Answers - eNotes.com|website=eNotes}}</ref> identifies the types of cost analysis used in policy making to aid decision process. These are: Cost-Benefit analysis, Cost-effectiveness, cost-utilization and cost utility.

===== Social cost-benefit analysis =====
Pathak (n.d.)<ref>{{Cite journal
| url = https://www.academia.edu/3848594
| title = Social Cost-Benefit Analysis: A Study of Power Subjects
| last = Pathak
| first = R
| date = n.d.
| website = Social Cost-Benefit Analysis: A Study of Power Subjects
| access-date = 29 February 2016
}}</ref> explains that Social Cost Benefit Analysis (SCBA) is also referred to as Economic Analysis (EA). SCBA or EA is a feasibility study of a project from the viewpoint of a society to evaluate whether a proposed project will add benefit or cost to the society (Ibid.). Ongkiko and Flor (2006<ref name="OandF" />) further elaborate that SCBA is a quantitative method which attaches monetary values on social conditions brought by certain communication policies. Flor (1991) explains the monetary value of the social costs is subtracted from the social benefits of a particular program or policy. A positive difference is required for a program or policy to be adjudged as socially beneficial.<ref name=":2" /> The purpose of SCBA is to assist public decision-making, not in terms of producing the ideal project but simply by proposing the optimum solution for the community out of the spectrum of possibilities (Dupuis, 1985).<ref name=":12">Dupuis, Xavier (1985). ''Applications and Limitations of Cost-Benefit Analysis as Applied to Cultural Development.'' A study commissioned by UNESCO. Retrieved online from http://unesdoc.unesco.org/images/0008/000819/081977eo.pdf [24 April 2016].</ref> Hence, the objective is to determine optimum quantities as a contribution to decision-making or to evaluate the effectiveness of decisions already taken.<ref name=":12" />

===== Problematique analysis =====
The problematique analysis procedure is a naturalistic approach<ref name=":13">{{Cite journal |doi = 10.1080/01292989309359574|title = Towards a methodology for problematique analysis: A philippine experience|year = 1993|last1 = Librero|first1 = Felix|journal = Asian Journal of Communication|volume = 3|pages = 84–102}}</ref> that seeks to discover the influential factors<ref name=":2" /> and describe the structure of problems that exist in communication systems (Librero, 1993; Flor, 1991). The basic purpose of this approach, according to Librero (1993), is to identify the problem rather than the solution. In the process, therefore, the evaluator employing problematique analysis identifies the factors that influence the system, shows the hierarchical relationships of these factors and traces the root causes of the problems of the system.<ref name=":13" /> Flor (1991) classified these influential factors as either ''subordinate'' or ''superordinate'', with the former being merely the symptoms of the latter. The identification of the superordinate influential factors or the root causes, then, prevents the recurrence of the problem situation.<ref name=":2" />

"Problematique" situation occurs when certain recurring problems come about due to the fact that symptoms are treated but not the root cause of such problems. When 'superordinate influential factors', root causes of problems, are identified and given focus, real solutions come about. This is done through a 'problematic map' (Librero, 1998), perceived as basic tool for problem analysis that basically identifies the root causes which can be the bases for forming solutions.<ref>Ongkiko, V. & Flor, A. (2006). Introduction to Development Communication. UP Open University.</ref>

===== Scenario construction =====
As a policy analysis tool, scenario construction (SC) describes a possible set of future conditions (Moniz, 2006<ref name=":9">{{cite book |chapter-url=https://www.researchgate.net/publication/200002555 |doi=10.1007/0-387-28829-5_9|chapter=Scenario-Building Methods as a Tool for Policy Analysis|title=Innovative Comparative Methods for Policy Analysis|year=2006|last1=Moniz|first1=António Brandão|pages=185–209|isbn=0-387-28828-7}}</ref>) or hypothetical events that may occur in the future of a particular system (Allen, 1978, as cited by Flor, 1991). It has also been defined as a description of the conditions and events under which some system being studied is assumed to be operating (Kraemer, 1973, as cited by Flor, 1991). Scenarios provide an educated description of one of many possible futures of a system, usually presented at the most optimistic or "best-case" state and the most pessimistic or "worst-case" state.<ref name=":2" /> According to Moniz (2006), the most useful scenarios are those that display the conditions of important variables over time. In this approach, the quantitative underpinning enriches the narrative evolution of conditions or evolution of variables; narratives describe the important events and developments that shape the variables. In terms of innovative methods for policy analysis, the foresight and scenario construction methods can be an interesting reference for social sciences (Moniz, 2006<ref name=":9" />). Citing Allen (1978), Flor (1991) enumerates six steps in scenario construction, namely: (1) defining the system; (2) establishing a time period for the system to operate; (3) defining the external constraints on the environment of the system; (4) defining the elements or events within the system that are likely to increase or decrease the chances of the system's meeting its goals and objectives; (5) stating in probabilistic terms the likelihood of the occurrence of the elements or events; and (6) conducting a sensitive analysis of the results.

===== Policy Delphi =====
The Policy Delphi, according to Flor (1991), is a variation of the Delphi technique. It is a tool for the analysis of policy issues seeking the involvement and participation of anonymous respondents (usually representatives of the different stakeholders of the policy). Herein, the desirability and feasibility of certain policies are assessed from the points of view of the different stakeholders.<ref name=":2" /> Meanwhile, according to Turoff (1975), the policy Delphi aims to create the best possible contrasting insights to resolve a major policy problem. Herein, the decision maker is interested on having a group that will give him options and supporting evidences where he can choose from for him to make a solution, rather than having a group that will produce the decision for him. ''"The Policy Delphi is, then, a tool for the analysis of policy issues and not a mechanism for making a decision"'' (Turoff, 1975).<ref name=":10">Turoff, Murray (1975). The Policy Delphi. In ''Harold A. Linstone and Murray Turoff (Eds.), The Delphi Method: Techniques and Applications.'' pp. 80–96. Online copy was accessed from http://is.njit.edu/pubs/delphibook/delphibook.pdf [24 April 2016]</ref> Turoff (1975) notes the challenging nature of policy Delphi as a means for policy analysis, "both for the design team and for the respondents" (Turoff, 1975). As a process, the policy Delphi undergoes the following six phases: (1) Formulating the issue; (2) Citing options; (3) Deciding preliminary stance about the issue; (4) Searching and getting reasons for disputes; (5) Assessing the underlying reasons; (6) Reassessing the options.<ref name=":10" />

As a methodology, Delphi is used for structuring a group communication process so that the process is effective in allowing a group of individuals, as a whole, to deal with a complex problem.<ref name=":10" /> As mentioned, one of the advantages of this technique is the involvement of stakeholders in the analysis which is imperatively instrumental in building a consensus among people who will be/are affected by the policy/project. In the Philippines, this has also been well applied in a study conducted by Dr. Alexander Flor and Dr. Felix Librero in the Southeast Asian Needs Assessment for a Global Open Agriculture and Food University.<ref name=":15" /> Recently, Haynes, Palermo and Reidlinger(2016) adopted a Delphi modified technique(James Lind Alliance Approach) in their study in exploring obesity prevention<ref>{{Cite journal|last1=Haynes|first1=Emily|last2=Palermo|first2=Claire|last3=Reidlinger|first3=Dianne P.|date=2016-09-01|title=Modified Policy-Delphi study for exploring obesity prevention priorities|journal=BMJ Open|language=en|volume=6|issue=9|pages=e011788|doi=10.1136/bmjopen-2016-011788|issn=2044-6055|pmid=27601495|pmc=5020738}}</ref> in Australia.

Flor (1991)<ref name=":2"/> emphasizes the incorporation of divergent stakeholders in communication policy making. That the State is not a lone actor in the creation of public policies as noted by the various stakeholders identified by Flor (1991), attesting to the fact that State actions do not occur in an empty space. Consumer involvement to policy making can therefore of paramount importance in helping create relevant policies vis-à-vis Gatung's (1979)<ref>Galtung, Johian. (1971). 'A structural theory of imperialism'. ''Journal of Peace Research'', 8 (2) pp.81–117.</ref> postulation of policies promoting "''horizontalization'' where exchanges occur between the centers and peripheries "on more equal terms"." In this regard, employing appropriate methods in policy research such would be necessary in 'light of the diversity of stakeholders involved, there is a possibility to broaden the scope of 'expertise' to share opinion across diverse perspectives including local communities' (Haynes, et al., 2016). Employing the Modified Policy-Delphi technique to crafting an all-inclusive communication policy include the following jusutification:
* The Policy-Delphi technique ability to explore consensus and dissent, rather than aiming to achieve consensus,
* As a flexible technique, it can be applied to various situations to map overlapping priorities from different perspectives and identify mutual priorities across stakeholder groups and therefore is a valuable exercise for investigating complex public issues
* The technique facilitates an in-depth investigation which may detect limitations, considerations and consequences of policy options which may enhance the value and success of policy implementation.
* The diversity of stakeholders involved makes reaching consensus on priorities less feasible but where mapping perspectives may identify mutual concepts behind the most agreeable options to inform future research and practice.
* The technique provides an opportunity for participants to contribute equally, and offers additional options and comments throughout; in this respect, it gives all participants, including consumers, a voice in the complex debate [equity in 'Voices']
The methodology outlined in Haynes et al. (2016)<ref>{{Cite journal |doi = 10.1136/bmjopen-2016-011788|title = Modified Policy-Delphi study for exploring obesity prevention priorities|year = 2016|last1 = Haynes|first1 = Emily|last2 = Palermo|first2 = Claire|last3 = Reidlinger|first3 = Dianne P.|journal = BMJ Open|volume = 6|issue = 9|pages = e011788|pmid = 27601495|pmc = 5020738}}</ref> paper align with Servaes (1986)<ref name="Servaes, Jan 1986 pp. 73">Servaes, Jan (1986). Participatory Communication (Research) from a Freirean Perspective. ''Africa Media Review'' 10 (1), pp. 73–91.</ref> reference to the application of Participatory Communication (Research) from a Freirean Perspective by positing that for dialectical and emancipatory process of action and reflection that constitutes the "process of ''conscientization,'' where an agenda instead of defined by an academic elite and programs enacted by a bureaucratic elite for the benefit of an economic or political elite, participatory research involves people gaining an understanding of their situation, confidence and an ability to change that situation" (Servaes, 1986).<ref name="Servaes, Jan 1986 pp. 73"/> Therefore, the notion of Participatory Communication stresses the importance of cultural identity of local communities, and of democratisation and participation at all levels – international, national, local and individual. It points to a strategy, not merely inclusive of, but largely emanating from, the traditional 'receivers'. However one needs not to romanticize the use of such 'equity' methods. Sarveas(1986)<ref name="Servaes, Jan 1986 pp. 73"/> had outlined the following caution:
* Participatory research can all too easily be utilized as yet another tool of manipulation by vested interests.
* While the approach strives towards empowerment, challenges existing structures, and is consequently ideological, rigidly prescribed ideologies must be avoided
* In addition, knowledge and perspective gained may well empower exploitative economic and authoritarian interests instead of local groups.
* Far from helping the process of liberation, if the researcher is not careful, he or she may only enable the traditional policy-makers and vested interests to present their goods in a more attractive package.
* Even the best intentioned researcher/activist can inadvertently enhance dependency rather than empowerment. If she/he enters communities with ready-made tools for analyzing reality, and solving problems, the result will likely be that as far as those tools are successful, dependency will simply be moved from one tyrant to another".

===== Simulations and modelling =====
Simulations and modelling recently become a useful tool policy analysis involving computers and software in creating a virtual representation of the scenario. Because it offers a systems view of the situation, the analyst or researcher can monitor how the players or variables interacts in the simulated environment. The purposes of simulations may vary to include education, research, design improvement and/or the exploration of the probable effect of different policy decisions.

Guyonne Kalbe(2004) identifies and distinguishes two types of simulation models: macro and micro levels. According to Kalbe, the macro-level is applied mostly for huge sectors of the industries. This macro simulation is usually applied by developed countries in order to assess and understand policy changes. On the other hand, the micro-level is used for a specific company using a sample of population when a need for more precised and focused information is its goal. In contrast to large-scale industries that use the macro-level approach, the micro-level is individualized.<ref>{{Cite journal|last=Kalbe|first=Guyonne|title=Introduction: The Use of Simulation Models in Policy Analysis|url=http://businesslaw.curtin.edu.au/wp-content/uploads/sites/5/2016/05/AJLE-v7n1-kalb-intro.pdf|journal=Australian Journal of Labour and Economics|date=30 January 2020 |volume=7|pages=1–12}}</ref>

Since problems in policy decisions are not linear by nature, computer simulations provides a concrete view of the situation and how the variables changes pace. These changes in behaviors are integral in developing policies. Steven Bankes(1992) explicates the use of computer simulation in policy decisions wherein models used in policy analysis provide arguments to illuminate options for policy decisions based on the result of computer simulated analysis.<ref>Bankes, S. (1992). https://www.rand.org/content/dam/rand/pubs/notes/2009/N3093.pdf</ref>

The methodology has been successfully used in development projects. Thorngate & Tavakoli(2009) mention fields where computer simulations has aided decision makers in assessing the context and solutions to specific problems. Among these include: the climate changes, effects of fiscal changes in economic policies, traffic regulations, health allocation resources, air regulations and crisis management to name a few.<ref>Thorngate, W., and Tavakoli, M. (2009). Simulation, Rhetoric, and Policy Making. Simulation & Gaming, Sage Publications. Volume 40 number 4. https://doi.org/10.1177/1046878108330539</ref>

It is noted that simulations and modelling could be based on artificial data generating process (DGP) or real live data from the environment for analysis. The real data derived from the environment is often called "big data" due to the significantly larger size. This is especially critical in the development communication discussion when there is prevalent use of digital communication technology in low and middle income countries (Taylor & Schroeder, 2015). The technologies in these countries include mobile phones and notebooks. These technologies emit data as a byproduct and have great potential to fill some of the problematic gaps encountered by country policy makers and international development organizations. There is research indicating that the use of big data represents an important complement to country level statistics (Taylor & Schroeder, 2015).,<ref>{{cite journal |last1=Taylor, L & Schroeder R |first1=L&R |title=Is bigger better? the emergence of big data as a tool for international development policy |journal=GeoJournal |date=2015 |volume=80 |issue=4 |pages=503–518 |doi=10.1007/s10708-014-9603-5|bibcode=2015GeoJo..80..503T |s2cid=154360975 }}</ref> better water quality modelling (Korfmacher, 1998)<ref>{{cite journal |last1=Korfmacher |first1=K. S |title=Water quality modeling for environmental management: Lessons from the policy sciences |journal=Policy Sciences |date=1998 |volume=31 |issue=1 |pages=35–54 |doi=10.1023/A:1004334600179|s2cid=189823529 }}</ref> and improved agricultural development (WESTERVELT, 2001).<ref>{{cite journal |last1=WESTERVELT |first1=J.D |title=Empowering stakeholders and policy makers with science-based simulation modeling tools |journal=The American Behavioral Scientist |date=2001 |volume=44 |issue=8 |pages=1418–1437|doi=10.1177/00027640121956764 |s2cid=145768863 }}</ref>

The use of big data can ensure a more accurate measurement of macro-economic data such as price track. The Billion Prices Project (BPP) initiated by MIT's Sloan School of Management challenges the Argentina government on the misleading inflation index report. It reported by very high inflation rate by the government's statistical institute which led to the fire of all government officials in the department a few years later. The actual inflation rate after the lay-off eventually stabilizes. The group in MIT decided to investigate what is going on by programming a web scraper to find prices for everyday goods posted on the web by the country's supermarkets. It scrapes many data on the web and is a financially affordable experiment. The outcome of the result led to an increased suspicion that Argentina's statistical agency was under pressure to level off inflation rate by higher order authority. The BPP proves to be influential because it produced an inflation index that was more intuitively reflective of perceptions and in real society than the government. It also provides an alternative set of perspective on economic trends which policymakers can use to make prudent finance policy decisions. There is an increasing need for major governments in the world to rethink how development statistics should be collated in order to craft better and finer public policy.

The simulation approach in policy science is beneficial to policy coherence on the sustainable development goals commonly called SDGs. The SGDs developed by United Nations has integrative nature which is suitable for integrative modelling techniques (Collste et al., 2017).<ref>{{cite journal |author1=Collste, D. |author2=Pedercini, M. |author3=Cornell, S. E. |title=Policy coherence to achieve the SDGs: Using integrated simulation models to assess effective policies |journal=Sustainability Science |date=2017 |volume=12 |issue=6 |pages=921–931 |doi=10.1007/s11625-017-0457-x|pmid=30147764 |pmc=6086251 |bibcode=2017SuSc...12..921C }}</ref> Collste and the researchers have shown in a Tanzania experiment that modelling approach towards SGDs can bring interlinks to the forefront and facilitate a shift to a discussion on development grounded in systems thinking. It brings the multitudes of possible feedback loops that shape a country's development especially those in developing country. The modelling approach in SDGs maps interlinkages and provide analysis about the resulting behaviour of different policy decisions. It also provide new casual pathways on investments in public projects.