chore(script): Update data description

scoping_review.qmd

@@ -490,10 +490,9 @@ Of these, {nr_relevant} have been identified as potentially relevant studies for
 
 <!-- {{++ FIXME: Update description for changing study pool ++}} -->
 
-The currently identified literature rises almost continuously in volume,
-with small decreases between 2001 and 2008, as well as more significant ones in 2012 and 2016,
+The currently identified literature rises somewhat in volume over time,
+with first larger outputs identified from 2014,
 as can be seen in @fig-publications-per-year.
-Keeping in mind that these results are not yet screened for their full relevance to the topic at hand, so far only being *potentially* relevant in falling into the requirements of the search pattern, an increased results output does not necessarily mean a clearly rising amount of relevant literature.
 
 <!-- {{++ FIXME: give full year scale ++}} -->
 
@@ -520,14 +519,15 @@ df_study_years = None
 
 Anomalies such as the relatively significant dips in output in 2016 and 2012 become especially interesting against the strong later increase of output.
 While this can mean a decreased interest or different focus points within academia during those time spans,
-it may also point towards missing alternative term clusters that are newly arising, or a re-focus towards different interventions, and should thus be kept in mind for future scoping efforts.
+it may also point towards alternative term clusters that are newly arising, or a re-focus towards different interventions,
+and should thus be kept in mind for future scoping efforts.
 
-Looking at the distribution between white and gray literature a strong difference with white literature clearly overtaking gray literature can be seen, a gap which should not be surprising since our database query efforts are primarily aimed at finding the most current versions of white literature.
-The gap will perhaps shrink once the snowballing process is fully completed,
-though it should remain clearly visible during the entire scoping process as a sign of a well targeted identification step.
+The predominant amount of literature is based on white literature, with only a marginal amount solely published as gray literature.
+This represents a gap which seems reasonable and not surprising since the database query efforts were primarily aimed at finding the most current versions of white literature.
+Such a stark gap speaks to a well targeted identifaction procedure, with more up-to-date white literature correctly superseding potential previous publications.
 
 @fig-citations-per-year-avg shows the average number of citations for all studies published within an individual year.
-From the current un-screened literature sample, several patterns become visible:
+From the literature sample, several patterns emerge:
 First, in general, citation counts are slightly decreasing - as should generally be expected with newer publications as less time has passed allowing either their contents be dissected and distributed or any repeat citations having taken place.
 
 ```{python}
@@ -535,25 +535,28 @@ First, in general, citation counts are slightly decreasing - as should generally
 #| fig-cap: Average citations per year
 bib_df["zot_cited"] = bib_df["zot_cited"].dropna().astype("int")
 grpd = bib_df.groupby(["year"], as_index=False)["zot_cited"].mean()
-ax = sns.barplot(grpd, x="year", y="zot_cited")
+fig, ax = plt.subplots()
+ax.bar(grpd["year"], grpd["zot_cited"])
+sns.regplot(x=grpd["year"], y=grpd["zot_cited"], ax=ax)
+#ax = sns.lmplot(data=grpd, x="year", y="zot_cited", fit_reg=True)
 ax.tick_params(axis='x', rotation=45)
 plt.tight_layout()
 plt.show()
 ```
 
-Second, while such a decrease is visible in relatively recent years (especially 2019--2023), it is not a linear decrease throughout but rather a more erratically stable citation output.
-This points to, first, no decrease in academic interest in the topic over this period of time,
-second, no linearly developing concentration or centralization of knowledge output and dissemination,
-and third potentially no clear-cut increase of *relevant* output over time either.
+Second, while such a decrease is visible the changes between individual years are more erratic due to strong changes from year to year.
+This suggests, first, no overall decrease in academic interest in the topic over this period of time, 
+and second, no linearly developing concentration or centralization of knowledge output and dissemination,
+though it also throws into question a clear-cut increase of *relevant* output over time.
 
 Positive outlier years in citation amount can point to clusters of relevant literature feeding wider dissemination or cross-disciplinary interest, a possible sign of still somewhat unfocused research production which does not approach from a single coherent perspective yet.
 It can also point to a centralization of knowledge production, with studies feeding more intensely off each other during the review process, a possible sign of more focused knowledge production and thus valuable to more closely review during the screening process.
 
-Or it may mean that clearly influential studies have been produced during those years, a possibility which may be more relevant during the early years (2000-2008).
-This is because, as @fig-publications-per-year showed, the overall output was nowhere near rich as in the following years, allowing single influential works to skew the visible means for those years.
+It may also suggest that clearly influential studies have been produced during those years, a possibility which may be more relevant during years of more singular releases (such as 2011 and 2013).
+This is because, as @fig-publications-per-year showed, the overall output was nowhere near as rich as in the following years, allowing single influential works to skew the visible means for those years.
 
-In all of these cases, such outliers should provide clear points of interest during the screening process for possible re-evaluation of current term clusters for scoping.
-Should they point towards gaps (or over-optimization) of sepcific areas of interest during those time-frames or more generally, they may provide an impetus for tweaking the identification query terms to better align with the prevailing literature output.
+In all of these cases, such outliers should provide clear points of interest during the screening process for eventual re-evaluation of utilized scoping term clusters and for future research focus.
+Should they point towards gaps (or over-optimization) of specific areas of interest during those time-frames or more generally, they may provide an impetus for tweaking future identification queries to better align with the prevailing literature output.
 
 <!-- {{++ TODO: Add breakdown by thematic area++}} -->
 
@@ -588,6 +591,10 @@ plt.show()
 by_intervention = None
 ```
 
+@fig-intervention-types shows the most often analysed interventions for the literature reviewed.
+Overall, there is a focus on measures of minimum wage and education interventions, 
+as well as collective action, subsidies, trade liberalization changes and training.
+This points to a spread capturing both institutional, as well as structural and agency-driven programmes.
 
 <!-- {{++ TODO: describe intervention types with complete dataset ++}} -->