- Provisiones para Activos de Riesgo

This part of the research comprises a content analysis of the science stories in news bulletins on Ireland’s public broadcaster RTÉ. These programmes were chosen for analysis because in the focus group part of the research, focus group participants talked about news television programmes being their main source of information about the world. The RTÉ Nine O’Clock News was chosen for analysis because it features consistently in the top twenty most watched television programmes in Ireland according to the TAM ratings, for example the TAM ratings for January–December 2011, show that RTÉ News: Nine O'Clock was the tenth most watched programme for that year (please see Appendix D for full details). RTÉ Nine O’Clock News is far ahead of its rival news programmes.

Rank & Programme AV TVR AV 000’s AV Share

1. The Late Late Toy Show 35.03 1195.3 65.19%

2. Eurovision Song Contest 29.96 1016.5 63.08%

3. All Ireland Senior Football Final 28.2 962.3 70.30%

4. The Frontline Leader's Debate 27.44 935 59.13%

5. Mrs Brown's Boys Christmas Special

24.9 849.6 48.72%

6. The Late Late Show 24.53 835.9 56.62%

7. Mrs Brown's Boys 24.43 832.5 52.04%

8. Prime Time Leader's Debate 23.16 789.2 49.80%

9. The Rose of Tralee 22.61 767.2 53.16%

10. RTÉ News: Nine O'Clock 22.56 769 44.15%

Source: Nielsen Television Audience Measurement / Arianna

Based on National, ROI Commercial Channels, January–December 2011, Consolidated

Table 4.2 TAM ratings for January–December 2011

Focus group participants also discussed how watching RTÉ News formed part of their everyday routine.

The RTÉ website makes available recordings of every RTÉ news bulletin dating back as far as 14 December 2008 at www.rte.ie/news/player/nine-news/. I began by watching three months of these news bulletins in order to get a rough idea of how many science stories were included and how big my sample would have to be to ensure manageability. I decided that my sample size needed to be a full year’s worth of programmes. This ensured that the programmes I watched covered a broad range of topics, and also took into account any seasonal variation in coverage of science (Irish television is seasonal, e.g. popular chat shows like The Late Late Show are not shown in the summer months, this also goes for news programmes, for example July and August are known as the Silly Season, because Dáil Éireann²⁰ is in recess and there are far fewer political news stories. I decided to watch every episode of RTÉ Nine O’Clock News for a year because many stories with a scientific aspect, for example food contamination risks or natural disasters are clustered about a few days or weeks, so using a random sample or even constructed weeks would perhaps not give a full picture of the frequency of science stories in RT_É News.

The coding instrument

The coding instrument used was based on that used for Mellor et al.’s (2011) report:

Content Analysis of the BBC’s Science Coverage for the BBC Trust. The decision to use similar coding categories to those used in by Mellor et al. was taken in order to allow for ease in comparing results with findings in the UK.

The data was captured and analysed using SPSS, as this is a software tool designed specifically for research in the social sciences and I had experience in using it to capture and analyse media content. To set up the SPSS template, I referred to the coding categories detailed in Appendix One of the Mellor et al. report, and used the relevant parts of it to create my coding sheet which is given in full in Appendix E. In SPSS, I set up a column for each category given in my coding sheet, and then

20 Dáil Éireann is the principal chamber of the Irish parliament.

assigned a numerical code to each possible option for all the categories. For example, for the scientific field category, the numerical codes were assigned as follows:

1 = Scientific field 2 = Physical sciences 3 = Life sciences

4 = Medical science & technology 5 = Climate science & technology 6 = Engineering & technology 7 = Mathematics

8 = Mixed 9 = Other

The unit of analysis was the individual story, including studio introduction, package and studio discussion as appropriate. News stories were first of all sorted into three

categories:

• science stories,

• stories which alluded to science

• not science stories.

For the purpose of this analysis, and again in order to facilitate comparison with UK BBC news programmes, I used the same definition of a science story as that

developed by Mellor et al. (2011), that is, to count as a science story, at least one of the following must form a significant component of the story:

• activities or findings from the natural sciences, the applied sciences, medical science, or mathematics;

• activities or findings which are referred to as scientific;

• references to scientific institutions;

• references to individuals who are identified as having scientific expertise either by virtue of their disciplinary base or by their institutional role;

• references to individuals who are identified as being “experts”, or “researchers”, or equivalent, where the implied subject of their expertise is the natural

sciences, the applied sciences, social science, medical science, or mathematics;

• the research and development stage of new technologies.

Stories which alluded to science were defined as those with a brief undeveloped reference to science (as defined above). Included in this category were any items which may be inferred to involve science or which may have a potential science angle, but where this has not been developed within the item beyond a brief reference, or stories which include explanation based on established scientific knowledge but which have not met the required criteria for a science item.

Stories which were not science stories were defined as stories with no reference to science; use of the word “science” or scientific terminology out of context without reference to scientific claims or activities; reference to facts which can reasonably be ascribed to general knowledge or to the standard knowledge base of professional practitioners (e.g., medical doctors, engineers).

I watched each news programme and each individual story in its entirety as I did not want to rely on the headline only to see if was a science story as I wanted to see if a non-science story alluded to science in any way, for example, a crime story could have had a forensic science element to it.

I noted the broadcast date of all the stories coded as science stories or stories which alluded to science. I did this so that I could navigate to them again easily as these stories were then analysed further.

Fr the next stage of the analysis, I returned to the science stories, and watched each one full screen on a desktop computer, frequently pausing and restarting to allow me to transcribe each story in full and to capture screenshots. I then watched the stories again and this time coded them using the SPSS template as described above. I entered the individual codes for each story into SPSS directly (on a laptop), using a hard copy of the coding sheet in Appendix E as a guide.

The content analysis measured:

• The prominence of science in the story

• The scientific field the story refers to

• They type of news event the story refers to (research, science policy, natural event/accident etc.)

• The reporter’s beat

• The gender of contributors to the story

• The expertise of the contributors

• The title of the contributors

• The affiliation of contributors

• Whether the story contained cautionary comments about the science

• Whether the story contained oppositional comments about the science

• The overall approach of the story (informational, questioning/investigative, light hearted)

• The tone of the story

• Whether the interviewer uses humour

• Whether the interviewer is aggressive in his/her questioning

• Whether the story gives links to a website

• Whether the experimental design is mentioned

• Whether controversy is indicated

• Whether uncertainty is indicated

• Whether a funder is indicated

• Whether a publication is indicated

• Whether peer review is mentioned