Analysis of Qualitative Material

Osnovni je cilj svake analize sadržaja pretvoriti pojavu (simbolično ponašanje ljudi) u znanstvenu činjenicu (podatak). Autor navodi četiri karakteristike koje mora imati znanstvena činjenica: 1) objektivnost i reproduktibilnost, 2) prikladnost za mjerenje i kvantifikaciju, 3) značaj za sistematsku teoriju, bilo »čistu« ili »primjenjenu«, i 4) svojstvo da se može generalizirati. U konstruiranju nacrta istraživanja poželjno je slijediti šest faza, od kojih je, svaka niz međuzavisnih odluka. Za svaku od tih faza potrebno je kontrolirati nacrt koji se razvija, s obzirom na formalne zahtjeve znanstvenih činjenica. Evo tih faza ili koraka: 1) specificiranje potrebnih podataka, 2) izrada plana tabeliranja, 3) izrada kostura nacrta analize, 4) popunjavanje kategorija za svaku varijablu, 5) utvrditi proceduru za formiranje jedinica (enumeracije, registriranja, konteksta), i 6) isprobavanje nacrta istraživanja i procedure istraživanja jedinica na primjerku materijala. Uspješna upotreba dobro razvijenog nacrta ovisi o izboru sposobnih kođera, njihovom treningu i nadzoru kodiranja. Iskustvo je pokazalo da, kada je tehnički dobro konstruirana, analiza sadržaja može biti od najveće koristi za istraživanje u društvenim znanostima. Uspješan istraživački projekat kombinirat će tehničku perfekciju s planom usmjerenim tako da dade odgovor na važne istraživačke probleme.The fundamental objective of all content analysis is to convert phenomena (i.e., symbolic behavior of people) into scientific data. Author has specified four characteristics which scientific data must display: (1) objectivity and reproductibility, (2) susceptibility to measurement and quantification, (3) significance for systematic theory, either »pure« or »applied«, and (4) generalizability. In constructing an analysis outline for a given project, it will be useful to organize the work so that it consists of six steps, or clusters of decisions. At each of these points the developing outline should be checked against the formal requirements for scientific data. These steps are: (1) specifying needed data, (2) mapping out plans for tabulation, (3) laying out the skeleton of the outline, (4) filling in categories for each variable, (5) establishing procedure for unitizing the material, (6) trying out the analysis outline and unitizing procedure on a sample of the material. The successful use of a well-developed outline depends upon the selection of capable coders, effective training of them in the outline being used, and the establishment of good supervision so that so that proper procedures of coding are followed. Experience over a number of years with content analysis reveals that when technically well executed it can be a most valuable tool for the social scientist. It should be viewed, however, only as a tool. Even when it is extremly well fashioned, its scientific or practical value may, in a specific project will combine both technical excellence and a good research design aimed at answering significant research questions

The number of paths and cycles in a digraph

An algorithm is presented for constructing from the adjacency matrix of a digraph the matrix of its simple n -sequences. In this matrix, the i, j entry, i ≠ j , gives the number of paths of length n from a point v i to a point v j ; the diagonal entry i, i gives the number of cycles of length n containing v i . The method is then generalized to networks—that is, digraphs in which some value is assigned to each line. With this generalized algorithm it is possible, for a variety of value systems, to calculate the values of the paths and cycles of length n in a network and to construct its value matrix of simple n -sequences. The procedures for obtaining the two algorithms make use of properties of a line digraph—that is, a derived digraph whose points and lines represent the lines and adjacency of lines of the given digraph.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45721/1/11336_2005_Article_BF02289506.pd

A note on a matrix criterion for unique colorability of a signed graph

A signed graph, S , is colorable if its point set can be partitioned into subsets such that all positive lines join points of the same subset and all negative lines join points of different subsets. S is uniquely colorable if there is only one such partition. Developed in this note is a new matrix, called the type matrix of S , which provides a classification of the way pairs of points are joined in S . Such a classification yields a criterion for colorability and unique colorability.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45725/1/11336_2005_Article_BF02289592.pd

Group Process and Organizational Environment: Student Organizations in the University

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68768/2/10.1177_089976407400300305.pd

Some Principles of Mass Persuasion: Selected Findings of Research on the Sale of United States War Bonds

http://babel.hathitrust.org/cgi/pt?id=mdp.39015071810167;view=2up;ui=fullscreen#page/n0/mode/2u

Analysis of Qualitative Material

Osnovni je cilj svake analize sadržaja pretvoriti pojavu (simbolično ponašanje ljudi) u znanstvenu činjenicu (podatak). Autor navodi četiri karakteristike koje mora imati znanstvena činjenica: 1) objektivnost i reproduktibilnost, 2) prikladnost za mjerenje i kvantifikaciju, 3) značaj za sistematsku teoriju, bilo »čistu« ili »primjenjenu«, i 4) svojstvo da se može generalizirati. U konstruiranju nacrta istraživanja poželjno je slijediti šest faza, od kojih je, svaka niz međuzavisnih odluka. Za svaku od tih faza potrebno je kontrolirati nacrt koji se razvija, s obzirom na formalne zahtjeve znanstvenih činjenica. Evo tih faza ili koraka: 1) specificiranje potrebnih podataka, 2) izrada plana tabeliranja, 3) izrada kostura nacrta analize, 4) popunjavanje kategorija za svaku varijablu, 5) utvrditi proceduru za formiranje jedinica (enumeracije, registriranja, konteksta), i 6) isprobavanje nacrta istraživanja i procedure istraživanja jedinica na primjerku materijala. Uspješna upotreba dobro razvijenog nacrta ovisi o izboru sposobnih kođera, njihovom treningu i nadzoru kodiranja. Iskustvo je pokazalo da, kada je tehnički dobro konstruirana, analiza sadržaja može biti od najveće koristi za istraživanje u društvenim znanostima. Uspješan istraživački projekat kombinirat će tehničku perfekciju s planom usmjerenim tako da dade odgovor na važne istraživačke probleme.The fundamental objective of all content analysis is to convert phenomena (i.e., symbolic behavior of people) into scientific data. Author has specified four characteristics which scientific data must display: (1) objectivity and reproductibility, (2) susceptibility to measurement and quantification, (3) significance for systematic theory, either »pure« or »applied«, and (4) generalizability. In constructing an analysis outline for a given project, it will be useful to organize the work so that it consists of six steps, or clusters of decisions. At each of these points the developing outline should be checked against the formal requirements for scientific data. These steps are: (1) specifying needed data, (2) mapping out plans for tabulation, (3) laying out the skeleton of the outline, (4) filling in categories for each variable, (5) establishing procedure for unitizing the material, (6) trying out the analysis outline and unitizing procedure on a sample of the material. The successful use of a well-developed outline depends upon the selection of capable coders, effective training of them in the outline being used, and the establishment of good supervision so that so that proper procedures of coding are followed. Experience over a number of years with content analysis reveals that when technically well executed it can be a most valuable tool for the social scientist. It should be viewed, however, only as a tool. Even when it is extremly well fashioned, its scientific or practical value may, in a specific project will combine both technical excellence and a good research design aimed at answering significant research questions