La metáfora de las voces en silencio como modelo para reforzar la autoestima

Searching for information

One common issue for participants was the difficulty they had in finding information they needed in either data packages or associated documentation. Several participants had used data that were “much more difficult to understand” (PS08) because they had a hard time finding the information they needed. PP01 said, “the data make me work really hard to get the

information I need, and there’[re] just times where I wasn’t sure it’s worth it.” In this case, the difficulty was not from a lack of documentation or information but because of the organization of the information. Another participant noted that one data set had “separate coding sheets that are not in their data dictionaries” (PP12). Neither PS15 nor PS14 were able to find items that were supposed to be in the sections they consulted, and they initially thought “maybe it was excluded for some reason, but it turns out it was elsewhere.” All three had to “seek out the information” and figure out where the information could be found in the entire data package “to add it back in” (PS14), which they found time consuming:

PS15: They have codebooks available, but it's very time consuming to really sit there and wade through it. And it's one of those things that you have to do due diligence to make sure that you don't overlook information that you want, and say it's not there when it actually is there.

Understanding codes

Sometimes the participants just did not understand the labels that the original

(PP12). PS08 said, “The codes were not intuitive” because “you can’t make guesses about what you think things mean.” Although there were codebooks, codes and labels that were readily understandable could have saved time and lightened the workload. PS08 recalled working with inappropriate codes, “spending much unnecessary time to understand the data,” but she still did her best because an incorrect understanding would only give “3,000 observations of numbers that are meaningless.”

Insufficient documentation

One of the greatest challenges participants discussed was insufficient information. A few participants had worked with data from individual researchers, accompanied by minimum information in data packages, occasionally even without codebooks. PS15 just received a

“paragraph about the methods, and had a paragraph, [that] maybe talks about the population” but did not receive “a codebook and a lot of demographic questions that they’ve been asked.” PS13 also received “only the major data files, there really isn’t a codebook,” and any other

documentation was “just very poorly described” with “some sort of abbreviation that you’re not exactly sure what it is.” Insufficient information made a participant feel that he “kind of ha[d] to know by myself” (PS13) and “assume it was coded this way, but I could be wrong” (PS15). Both of them eventually used these data sets because they trusted the credentials of the original

investigators and thought that the poor documentation was not relevant to the original investigators’ intention, but “they just didn’t document more than that” (PS15), not even considering the possibilities of data sharing, which PS13 thought was “very unfortunate.”

Because of the lack of information and poor documentation, both participants spent time figuring it out by themselves, but they would have liked more information about the data.

PS15: It was enough for publication purposes, but it's not... I don't know, maybe I'm just being overly cautious, but as a researcher, I'd really want to know where the data came from and how it was collected.

PS15 later gathered information directly by “talking to [the original investigator] and learning more information from that.” However, because PS15 had to rely on “having them try to recall and think back to what they did,” he considered the information “limiting.”

Even if participants worked with well-documented data, sometimes they still wanted additional information. PP10 said:

PP10: You don't necessarily understand everything that was done in the study, and so you do have to ask a lot of questions and make sure that you have a really good understanding of what they did because otherwise it's very difficult to write up the methods and exactly what [they] did. (…) It's difficult to write up all those details unless you have a really good working understanding of them.

Others noted that “there wasn’t enough information like I wanted” (PP13); “I just wanted to know a little more about their samplings to understand how they did [it] and why they did [it]” (PP15), and wanted to know “the logic behind their decision” (PS07). What PP10 and many others discussed is consistent with the literature, which notes the inherently insufficient nature of documentation and the limitations of knowledge transfer from the original data creator to

subsequent data re-users. In addition, due to the variance in participants’ experiences and the tacit knowledge needed to interpret data documentation, some may have needed more

3.3.2. Process of trust development: Provisional trust judgment