T his book rests in part on a foundation of data collected about television

programming in several countries around the world. These data are discussed at length in Chapters 6 and 7.

Methodology The data for this study were generated through a simple content analysis of

television listings in TV guides and newspapers during sample periods since

1 962. Each program was categorized, and the number of minutes each pro gram lasted were added up to create a total number of minutes for that category. Categories were located in a matrix between program types/genres

(news shows, variety shows, etc.) and program sources (national, regional, U.S., other international, coproduction). The genre subcategories were orig inally developed during studies in the Dominican Republic and Brazil; the genre categories used by industry experts were compared with genre cate gories that emerged from in-depth interviews with audience members. The resulting list of genres was valid in terms of being accepted by both creators and consumers of television and reliable across interviewees in both coun tries. As countries were added to the sample, care was taken in further cod ing, particularly in countries outside Latin America, to make sure that the same overall genre categories still applied.

In the data, prime-time broadcasting is distinguished from the total broadcast day. This strategy permitted a rough measure of which programs were relatively more popular because in all countries used in the study, the

258 World Television

most popular programming tended to be concentrated in that period of time when, by definition, the most people were watching. Local designations of prime time varied, depending on the national culture and habits, but they generally fell between 7 p.m. and 1 1 p.m. This prime time vs. total broadcast day distinction was used in a study of Brazil by Straubhaar ( 1 9 8 1 ) and i n the second round of the UNESCO study b y Varis and Nordenstreng ( 1 985). It has proven useful in isolating the programming intended to be most widely viewed, typically reflecting the programmer's anticipation of what will be most popular (Havens, 2006).

Participants or coders were selected for their familiarity with program names, types, and sources over time. Coders were trained in categorizing programs by genre and by country of origin. The coders were initially

treated more as a panel of experts than as a set of interchangeable coders in a standard content analysis. They consulted with other people from their respective countries to make sure that the accepted definitions of genre cat egories applied within their country or culture. Substantial agreement was sought before coding the category definitions; in addition, an intercoder reliability analysis was conducted for subsamples of the coded schedule in all but two of the initial countries. Intercoder reliability exceeded 90%, which is not surprising, given that the coding was quite basic: simply cate gorizing programs by commonly accepted genre definitions and by country of origin. When coders had any doubts about how to identify or categorize

a program by genre or origin, they contacted other people from that country to make sure that they had correctly identified the type and source of the program. A list of standard genre category descriptions, or coding instructions, was created and used, although for some countries, categories emerged that did not fit in the overall pattern of genres.

Sample Sample countries are drawn _ from six geocultural or cultural-linguistic areas:

Latin America (including the US-Hispanic cultural market), the Anglophone (English-speaking) nations and cultural markets (including Anglo-Canada),

Asia, Europe, the Middle East, and Africa. In Latin America, a regional market has been well-developed for decades; in East Asia, national production has been strong, and regional production seems to be developing; in Africa, a regional market might be logical, but as yet, countries are having little national produc tion or regional exchange. Countries were selected to represent a diverse range of market sizes and production abilities within those six regions of the world.

� The sample periods are one week in March or November in 1 962, 1 972,

/ 1982, 1 99 1/1 992, and 2001/2002; that is, five 1 -week periods. (When this

Appendix 259 Some scholars now argue that at least 2 weeks per year is necessary, but

lacking the staff or financial resources to redo early data, 1 -week samples were used for comparability.) Some minor variations took place, particularly in the 1960s and again in 2001/2002. Data from Brazil were available

for 1963, 1971, and 1 9 8 1 , not 1962, 1972, and 1982. Overall, the dates provide some comparability with the Nordenstreng and Varis UNESCO studies, done in 1972 and 1 982. When a country did not yet have television in 1962, the first data were collected in the first year of broadcasting, when ever that was, and then in the ensuing regularly sampled year. Copies of TV

guides and newspapers were obtained from libraries in hard copy or in microfilm/fiche. Some countries were coded during 1999, some in 2001 , and

a few in 2002, depending on material resources and when coders were avail able. Despite these minor variations, the data will be presented as though they were collected every 1 0 years beginning in 1962.

Region Sample Nations Years When Data Were Collected Latin America

Brazil 1963, 1971, 1 98 1 , 1991, 2002 Chile

1962, 1972, 1982, 1991, 2001 Columbia

1962, 1972, 1982, 1991, 2001 Mexico

1962, 1972, 1 982, 1991, 2001 U.5.-Hispanic

1972, 1982, 1991, 2001 Venezuela

1962, 1972, 1982, 1991, 2002 Anglophone

Australia 1962, 1972, 1982, 1991, 2001 Anglo-Canada

1962, 1972, 1982, 1991, 2001 Ireland

1962, 1972, 1982, 1991, 2001 New Zealand

1962, 1972, 1982, 1991, 2001 United Kingdom

1962, 1972, 1982, 1991, 2001 United States

1962, 1972, 1982, 1991, 2001 East Asia

China 1962, 1973, 1982, 1991, 1999 Hong Kong

1962, 1972, 1982, 1991 India

1972, 1982, 1991 Japan

1962, 1972, 1982, 1991, 1999 South Korea

1962, 1972, 1982, 1991, 1999 Taiwan

260 World Television ( Continued)

Region Sample Nations Years When Data Were Collected

Europe France 1 962, 1 972, 1 982, 1991, 2001 Italy

1962, 1 972, 1 982, 1 992, 1 999 Franco-Canada

1 962, 1 972, 1 982, 1 991, 2001 M iddle East

Israel 1 972, 1 982, 1 991 Lebanon

1 962, 1 972, 1 982, 1991 Africa

Cameroon 1991, 1 999 Nigeria

Within each country, not all broadcasting stations are represented. One major city in each country was selected as a sample. Particularly in Latin America, some minor channels represented nonmainstream patterns of programming, which might distort the validity of the kinds of television that were actually being watched. Stations that had less than a 5 % share of the audience, according to local ratings data, were therefore excluded. In Brazil, validity checks compared all stations with those that had more than

a 5% audience share. The result was exclusion of some government sta tions, some educational stations, and some very minor, usually new, com mercial stations, which did tend to use much more U.S. programming than

other stations. I decided that including those stations would overstate the effective presence of U.S. programming in Brazil. For this very reason, some earlier research used weighted-measure audience hours to reflect media absorption more accurately, with hours being weighted by ratings to indi cate actual audience viewing habits (Antola & Rogers, 1 984; Straubhaar,

1 9 8 1 ; 1 984), but that measure was impractical in this phase of the study because the ratings data for all of the countries and years are not available. Readers may note that the trends seen here correlate with those observed in the audience-hour studies in Latin America (Antola & Rogers, 1984; Straubhaar, 1 9 8 1 ; 1 984), another indication of general validity. The U.S.-Hispanic data is based on Spanish-language Channel 26 in Chicago.

T his book rests in part on a foundation of data collected about television