## 3 Research Design
### Codebook Construction  
In this study, coding means transforming each job ad into a \"bag-of-competencies\" (a sparse vector of occurrence of competency tags). As job ads have been transferred into multiple bags of stemmed words (each recording unit corresponds to a bag of stemmed words) in data preprocessing, a codebook in this study is consist of serval rule-based classifiers. Each classifier may judge whether a job ad requests a certain competency. A classifier contains a number of rules, each of which contains a word set and a corresponding competency tag (a competency tag is usually correspo). Different rules belonging to the same classifier contain different word sets and the same competency tag. Figure 4 shows part of the final codebook in this study. For rule \"**Analytical, problem solving skills**: analyz; problem\", if \"analyz\" and \"problem\" appear in one recording unit (the recording unit has been transferred into a bag of stemmed words) at the same time, it is said that the recording unit meets the rule and we may add a competency tag of **Analytical, problem solving skills** to this recording unit. If any recording units in a job ad own a competency tag of \"**Analytical, problem solving skills**\", it is concluded that the job ad requests a competency of **Analytical, problem solving skills**. All classifiers in the codebook will be applied to a job ad in turn to transform it into a bag of competencies. Figure 3: Example for context unit and record unit. Figure 2: Data flow diagram of pre-processing. The data flow diagram of the codebook construction is shown in Figure 5. _ALA's Core Competences of Librarianship_ divides core competencies of librarianship into 8 categories: **Foundations of the Profession**, **Information Resources**, **Organization of Recorded Knowledge and Information**, **Technological Knowledge and Skills**, **Reference and User Services**, **Research**, **Continuing Education and Lifelong Learning**, **Administration and Management**. The authors categorize themes used in [PERSON]'s codebook following the criterion, and categorize qualifications like second post-graduate degree as **Qualification** (see Table 1). Then, the authors manually construct a competency tag, a detailed explanation and a set of rules for each competency themes according to their samples. Each rule in the codebook grows from one meaningful stemmed word (like \"collect\", which indicates competencies related to \"collection\") and one temporary competency tag. However, a rule with only one stemmed word may get a low hit rate. To extend the rule, the authors manually pick other stemmed words one by one, making the rule more accurate. When the rule becomes accurate enough, the competency tag for the rule will be determined (either an existed tag or a new one). Of special note is that the rule may grow in multiple branches (see Figure 6). The selection of \"meaningful stemmed words\" is based on an assumption that if a meaningful word or phrase may compose a rule, it will appear much more frequently in recording units belonging to the corresponding theme than in other recording units. After applying a codebook to all recording units, we may add multiple competency tags for each of them. To simplify the definition, we add a special tag called \"None\" to recording units without any competency tags so that all recording units own at least one tag. Supposing \(C\) (contains \(c_{1}\), \(c_{2}\)... \(c_{n}\)) is the set of all competency tags in the codebook, \(R\) stands for all recording units, \(R_{ci}\) stands for recording units with tag \(c_{i}\). For each stemmed word in all recording units, the authors may calculate n TF-IDF (term frequency-inverse document frequency), each of which responds to a competency tag. Suppose \(w\) is a stemmed word, \(RC_{ci,w}\) stands for the number of recording units containing \(w\) and belonging to \(R_{ci}\). Define the importance of \(w\) as follows:  
\[I_{w}=\max_{c_{i}\in C\text{ }and\text{ }E_{ci,w}=0}\{tfidf_{ci,w}\}\]  
\[E_{ci,w}=