The extracted texts of the guidelines were adapted and standardised for analysis using the software Alceste.

Alceste® is textual or statistical data analysis software, originally designed by Max Reinert, of the CNRS, in France (Reinert 1990; Reinert 1993). Its use spread to the human and social sciences field in the 90s. It functions by way of frequency vocabulary count and helps to obtain analysis units that are based on formal criteria. It uses an inductive and recursive approach and helps to identify co-occurrences, or word associations in a sentence, using a treatment that is based on word resemblances and differences. Technically, Alceste® breaks the corpus into fragments that are relatively similar in size, referred to as “context units” (e.c.u.)[1]. These same fragments are then reclassified statistically and split into classes that are as differentiated as possible in terms of their specific vocabulary level. This classification is meant to split statements into classes marked by the contrast of their vocabulary, and thus opposed to one another (Kalampalikis 2003). These classes are called “lexical worlds” and are deemed to present an “idea” of the representations contained in the text as well as the main ideas and themes of the corpus (Garric & Capdevielle-Mougnibas 2009). Secondly, it defines a “mapping” of what the software developers called “contextual variables”[2]. These “variables” serve to identify texts and are related to their content. They are introduced by the researchers according to their relevance to the research questions. The classes highlighted by the software must then be examined and linked to the co-occurrences to give them meaning and explain their differences (Aubert-Lotarski & Capdevielle-Mougnibas 2002).

The texts were tagged according to author, year, discipline, the content coding, epistemology, number of categories, and number of subcategories (Appendix 5. Table of criteria selected for lexical analysis using Alceste). Processing the corpus with Alceste® resulted in its distribution into six distinct classes, integrating 67% of the total corpus (Appendix 6. Alceste report).

[1] Elementary context units (e.c.u.) defined by Alceste are the smallest statistical unit created by the software, based on a compromise between the syntactic form (proper punctuation) and the statistical constraints (these units must be of comparable size).

[2] Contextual variables are data elements known by the researchers and used as instructions for the software so that the lexical analysis can be conducted with these variables in mind.

Results Phase II