Algunas conceptualizaciones sobre la prostitución

Data analysis refers to the process of reducing, organizing and giving meaning to the data (Burns, N & Grove 1993). How one approaches the task of data analysis depends on the type of data gathered and conceptual framework employed (Wilcox 1982). The data in this study was descriptive constituting a record of DWU’s manifest behaviour as was observed by the researcher, perceived by the staff and related in interviews and contained in documentary material. Since culture, as is suggested here, was conceptualized as something that was embedded or below the surface, the analysis of data served to uncover the values, beliefs, norms or taken for granted assumptions that were embedded in the data.

In processing the data in this study, the data was coded using NVivo, the qualitative data analysis software. Coding refers to the process of reducing data and involves segmenting or chunking, tagging, sorting, discarding and organizing data (Bogdan & Biklen 1998; Miles & Huberman 1984). The process also allows the researcher to sharpen and focus data in order for links to be made across data batches or segments so that relationships, and thematic patterns that surface to be compared across the data sources (Miles & Huberman 1984; Wolcott 1994). It also allows for conclusions to be drawn and triangulated (Goetz & LeCompte 1984; Miles & Huberman 1984). In

this study, coding allowed for the latent and salient cultural themes to emerge in order conclusion to be drawn.

4.5.1 Determining Coding Categories

The process of coding requires that first categories to be used as tags to label data segments be determined (Bogdan & Biklen 1998; Tesch 1990). These tags serve as categories under which to shift and sort data. They can consist of recurrent “words”, “phrases”, “patterns of behaviour”, or “subjects’ ways of thinking” (Bogdan & Biklen 1998, p. 171). How one arrives at the preliminarily coding categories depends on the individual researcher (Tesch 1990). However, coding categories may also be drawn from the researcher’s perspective (Bogdan & Biklen 1998). This is because as Wilson (1977) and Wilcox (1982) explain, the researcher does not begin research as a “tabula rasa” but with a foreshadowed problem in mind.

The initial coding category tags to use in data analysis of this study were arrived at through both the reading of the data as well as the through the review of literature on the university and organizational culture. With these categories as tags, the

qualitative data analysis software, NVivo, was used to segment or chunk and label the data. But, it was not a straight forward process as there was an ongoing need to refine the codes or data categories. It is an inherent part of the process writes (Tesch 1990) for a new batch of data, for instance, one interview transcription, may question the appropriateness of the existing categories and so necessitate redefining which may entail renaming, modification in content, subdivision discarding or supplementation by new codes. The refining process only stops when the researcher is satisfied that the data converges with the organizing system (Tesch 1990).

The process of coding adopted in this study is illustrated below. The data was segmented under the data category of organizational practices that were HR related and specifically, related to reward and motivation. The type of reward and motivation was driven by intrinsic rewards which when triangulated with other data, points to the belief in service understood as altruism that is a value driving practice at DWU.

Data Segment from an Interview

Initial Coding category Latent Culture value Influence

The rewards are, for me, in my experiences …over here is to see my students getting out there and being

involved in seeing them perform out there, in our case, the media scene and I get a lot of satisfaction out of that making my students being on EMTV or

speaking over the radio or writing for the newspapers. And also the fact that I mean ah…in journalism I like, I like …to get involved at the beginning end of …is most satisfying than the rewards of…material rewards.

HR-Reward and Motivations

Service as altruism

This list below presents the primary themes and sub-themes which served as coding categories that facilitated the segmentation of the data in NVivo. The data segments tagged with these themes and sub-themes constituted what could be described as categories of artifacts of DWU culture. These artifacts were the surface indicators of deeper level values and beliefs at work in shaping and informing all aspects or DWU’s behaviour. The values and beliefs informed, for instance, how staff

responded of organizational participants to authority; how policies are implemented; what motivates staff to commit to the organization, which goals and functions are made subordinate.

T

S

-

Decision-making centralized

Participatory

HR-Practices and Process Reward and Motivation

Staff Development

Ranking and Promotion

Recruitment and Selection

Staff turnover

Organizational Goals Teaching

Research Service Market Religious

Academic Work Teaching

Service Research

Fundraising Mentoring

Pastoral care

Academic Concerns Course quality

Student learning

Resource support

Organizational purpose

Change engagement

Staffing

Reward and motivation Workload

Organizational Values Service

Partnership and Teamwork

“Open to All” Initiative

Organizational Change Governance Structure

Academic Policies

Organizational Expansion

“not standing still”

Organizational Events Calendar events

Infrastructure commissioning

Organizational Visitors National

International

Resource Support Academic work Support

Physical infrastructure support

Behaviour towards authority contestation

compliance