## 4 Results and Discussion
Moreover, the results above (Table 3) emphasized some peculiarities of these three regional models, namely the highly significant negative influence of laziness and the significant positive one associated with the total number of jobs for the respondents from MB; the positive ones corresponding to optimism and a perspective with a lot of opportunities and also to the urbanity level in the case of OMD (the Romanian capital, Bucharest, belongs to this region); finally, the positive ones of openness and stable career, being retired after the first job (_ret_work_aft_1_st_job_) for the respondents from TBCM. In addition, the influence of laziness seems to behave in opposition when considering TBCM (positive influence) and MB (negative influence on full job satisfaction, as the chosen outcome). Moreover, TBCM is the only region in which the influence of loneliness on the outcome appears and shows a negative sign. The use of Zlotnik probability prediction nomograms ensured more visual support for comparability and served for interpretations directly in probabilistic terms, including the automatic computation of the maximum probability thresholds for the most advantageous combination of values for predictors. After dragging imaginary perpendiculars intersecting the first X axis (Score) and summing up the scores from the nomogram above (Figure 2, the regional model of Moldova and Bucovina) for the seven identified influences in the most optimistic combination, we obtained a total (total score axis) of almost 26.2, as the sum of 2.8, 10, 2, 1.7, 3.3, 1.4 and 5. The latter value corresponds to a high probability of full job satisfaction (more than 99%, as automatically indicated under the form of a maximum percentage threshold on the right of Figure 2) and is derived based on a scenario with a very good accuracy of classification (value for the area under the ROC curve = 0.9173) and explanatory power (Pseudo R-square = 0.45, Table 3, scenario a). Figure 2: Full job satisfaction prediction nomogram for a regional model (Table 3, scenario a), corresponding to the first Romanian historical region being analyzed (MB). In a similar way, the maximum resulting probability of full job satisfaction (Figure 3) for the regional model of Transylvania, Banat, Crisana and Maramures was still high (much more than 95%, corresponding to a total score of almost 22, as a sum of 4.1, 10, 1.2, 2.7, 1.7, 1.2 and 1.1 for the seven influences above). Moreover, this probability is derived based on a scenario with a very good accuracy of classification (ROC = 0.905) and explaining power (Pseudo R-square = 0.4327, Table 3, scenario b). After summing up the scores from the nomogram (Figure 4, the regional model of Oltenia, Muntenia and Dobrogea), including the seven significant influences, we obtained a total score of more than 17.5 (the sum of 2.25, 10, 2, 1.25, 1.2 and 0.8). This score corresponds to a high probability of full job satisfaction (more than 95%) and is derived based on a scenario with only six influences and a very good accuracy of classification (ROC value = 0.9157) and explanatory power too (Pseudo R-square = 0.4553, Table 3, scenario c). We consider that the familial financial well-being could be an interesting predictor of job satisfaction. We believe that a better off economic situation of a family may exert a positive influence on career satisfaction due to increased psychological comfort, greater confidence in personal abilities and aptitudes and lower fear related to career uncertainties and evolution. Figure 3: Full job satisfaction prediction nomogram for a regional model (Table 3, scenario b), corresponding to the second Romanian historical region being analyzed (TBCM). All three nomograms (Figures 2-4) and the influences expressed in terms of marginal effects (Tables 1-3) indicate the prevalence of the influence associated with _colleag_good_atmosph_, when we analyzed full job satisfaction.