Transcribing and translating data

This section explains the transcribing and translating of the data. Since the data from fieldworks was in the form of audio files, it required transcription. The MPEG Layer-3 audio files were transcribed verbatim by the researcher and saved as rich-text- format (rtf) files. There were several benefits to the researcher performing the transcription him self, such as the greater familiarity with the data, that it brought, with the similarities and differences between different participants‘ accounts. This step was followed by translating the transcripts of the interviews and participative observation from bahasa to English. To ensure the validity of translation and to keep the contextual meaning of the data, the translation process was performed by the researcher with support from professional translator who signed a copy of a confidentially agreement.

4.7.2 Coding

The next stage was coding a from of data analysis that pattern within abundant data (Auerbachand & Silverstein 2003). Coding is acknowledged as a formal representation of analytic thinking about qualitative data (Miles & Huberman 1994; Ryan & Bernard 2000; Auerbachand & Silverstein 2003; Hesse-Bibber &

Leavy 2006; Marshal & Rossman 2011). Miles and Huberman(1994) viewed coding as an analysis to differentiate, combine and reflect on the data gathered from fieldworks: Hess-Biber and Leavy (2006) and Auerbach and Silverstein (2003) highlighted that coding may help the researcher locate key themes, patterns, ideas or concepts that may exist within the data.

Ryan and Bernard (2000) described the fundamental tasks related to coding:

identifying themes, building s codebook, marking text and constructing a model. The sampling was performed through the identification of a corpus of text and the selection of a unit analysis within the text: the identification of themes was carried out before, during and after data collection. A codebook was constructed to organise codes (labels or tags conveying meaning that could be in the forms of words, phrases, sentences or paragraphs). Codes were designed as tags to mark off text and as values assigned to fixed units. The last step was to seek the linkages among them by building a theoretical model (Miles & Huberman 1994).

In this study, the researcher performed the following data-analysis procedures:

(1) Reading through data. The researcher reflected on the overall meaning to gain general sense of the information and ideas that participants conveyed.

(2) Analysis through coding. The material was organised into segments by taking the text data and grouping sentences into categories, then labelling those categories with terms based on the actual language from participants.

(3) Using the coding process to generate codes for the description and generalisation of a small number of categories or themes. The researcher analysed the themes that emerged and gathered the two cases into a general;

description for the bounded case.

(4) Advancing the representativeness of the description of the themes by merging the emergent themes into a narrative passage, so that the findings came logically from the participants‘ responses.

(5) Interpreting the meaning of the data by focusing on what the participants were saying, the conclusions they drew and their intentions for future practices 4.7.3 Research steps

The research performed for this study followed a standard protocol to ensure that the interviews yielded data consistent with the study‘s goal:

(1) Initially, the participants were approached through phone calls or workplace visitations. The research project was explained to the participants in writing (using a participation Information Sheet, shown in Appendix 3) and orally. In turn, they were asked to voluntarily participate in the study by completing and

signing the Consent Form. If they were not willing to sign form, their oral responses the consent form will were recorded.

(2) In-depth (semi-structured) interviews were held with participants in their respective offices.

(3) Interviews were audio-recorded and transcribed within a day of the interview (4) Follow up informal contacts were initiated, and each participant was given his

or her respective transcript for member-checking and to verify transcript content.

(5) Government officers and representatives of trade associations were interviewed to gain government perspectives and industry perspectives.

(6) Secondary data in the forms of legal documents and study reports at the local and sub-national level were reviewed the researcher.

(7) The researcher coded the data for emergent themes.

4.7.4 Research credibility: validity and reliability

No single research paradigm claims superiority in the quality of research: both quantitative and qualitative have their own assumption basis for credibility. The good qualitative research have long been intensively discussed by scholars, such as Guba (1981), Miles and Huberman (1994), and Mason (1996). Most argued that the credibility of a qualitative inquiry could be examined through its trustworthiness, using various reliability and validity criteria. Guba(1981) further listed four:

credibility, transferability, dependability and conformability. Miles and Huberman (1994) underscored these aspects by broadly discussing five main issues about the trustworthiness of qualitative inquiry: the objectivity/conformability of qualitative work, reliability/dependability/auditability; internal validity/credibility/authenticity;

external validity/transferability/fittingness; and utilisation/application/action orientation.

Mason (1996) listed three elements by which qualitative research is generally judged: reliability and accuracy of method; validity of data; and generalizability of analysis. Reliability and accuracy of method ensures and demonstrates to others that data generation and analysis not only answer the question but is also thorough, careful, honest and accurate. Validity of data that can refer to the both the data generation method and the data interpretation, and judges whether the researcher

measured and explained what he or she claimed. Generalizability of analysis including empirical and theoretical generalisation refers to the extent to which the explanation has any wider resonance outside of the context being studied. Table 4.1 merges into two: validity and reliability. How these main criteria were addressed in this study is explained in next section.

Table 4.1

Source Guba(1981), Miles and Huberman(1994), and Mason (1996)