feat(script): Add robustness by region section

scoping_review.qmd

@@ -1166,6 +1166,9 @@ The authors suggest the primary channel is the newly increased bargaining power
 
 # Discussion & policy implications
 
+## Robustness of evidence
+
+
 ```{python}
 #| label: prep-inequalities-crosstabs
 # dataframe containing each intervention inequality pair
@@ -1196,12 +1199,11 @@ def crosstab_inequality(df, inequality:str, **kwargs):
     return tab.drop(tab[tab[inequality] == 0].index)
 ```
 
-As can be seen in @fig-region-counts, taken by region for the overall study sample,
-the evidence base receives a relatively even split between the World Bank regional country groupings.
+### Regional spread
 
-Studies tend to base their analyses more in national comparative studies for the North American and Europe and Central Asian regions, while relying more on case studies restricted to a single country context for developing countries in other regions, though this trend does not hold strongly everywhere or over time.
-A slight trend towards studies focusing on evidence-based research in developing countries is visible, though with an overall rising output, as seen in @fig-publications-per-year,
-and the ability for reliance on more recent datasets, this is to be expected.
+As can be seen in @fig-region-counts, taken by region for the overall study sample,
+the evidence base receives a relatively even split between the World Bank regional country groupings with the exception of the Middle East and North Africa (MENA) region,
+in which fewer studies have been conducted.
 
 ```{python}
 #| label: fig-region-counts
@@ -1229,6 +1231,23 @@ def regions_for_inequality(df, inequality:str):
     return sns.countplot(df_temp, x="region", order=df_temp["region"].value_counts().index)
 ```
 
+Most studies come from a context of East Asia and the Pacific, though with an almost equal amount analysing Europe and Central Asia.
+With slightly fewer studies, the contexts of North America, Sub-Saharan Africa follow for amount of anlalyses,
+and in turn Latin America and the Caribbean and South Asia with an equal amount of studies for each region.
+
+The lower amount of studies stemming from a MENA context can point to a variety of underlying causes:
+First, it is possible that there is simply not as much evidence-based analysis undertaken for countries in the region as for other national or subnational contexts,
+with research either following a more theoretical trajectory, or missing the underlying data collection that is available for other regional contexts.
+
+However, it cannot be ruled out that the search protocol itself did not capture the same depth of analytical material as for other contexts,
+with each region often having both a specific focus in policy-orientations and academically,
+and in some cases also differing underlying term bases.
+Such a contextual term differences may then not be captured adequately by the existing query terms and would point to a necessity to re-align it to the required specifics.
+
+One reason for such a differentiation could be a larger amount of gray literature captured compared to other regions,
+which may be utilising less established terms than the majority of captured literature for policy implementations.
+Another reason could be the actual implementation of different policy programmes which are then equally not captured by existing term clusters.
+
 ```{python}
 #| label: fig-validity
 from src.model import validity
@@ -1244,6 +1263,8 @@ g = sns.PairGrid(validities[["internal_validity", "external_validity", "identifi
 #sns.scatterplot(data=validities, x='external_validity', y='internal_validity', hue='intervention')
 ```
 
+### Inequality types analysed
+
 Policy interventions undertaken either with the explicit aim of reducing one or multiple inequalities, or analysed under the lens of such an aim implicitly, appear in a wide array of variations to their approach and primary targeted inequality, as was highlighted in the previous section.
 To make further sense of the studies shining a light on such approaches, it makes sense to divide their attention not just by primary approach, but by individual or overlapping inequalities being targeted, as well as the region of their operation.
 <!-- TODO have calculation for amount of studies w/ implicit/explicit targeting? -->