Table 7. The code of a small iDSL process with an EDF Section Process ProcessModel image_processing_application seq { atom edf_values load EDF with values 6 8 10 atom edf_files load EDF from file "measurements.dat"
Table 7. Overview of pre- and post-2012 WP activities at LSE Age group (school year) Pre-2012 activity 2012 and 2013 activity 2014, 2015, 2016 and 2017 activity Pre 14 (Years 6 to 8) Moving On Student tutoring Student mentoring Black Achievement Conference Introduction to the Social Sciences Promoting Potential Spring/Summer School (for African- Caribbean boys) Develop and improve programmes and maintain numbers on existing outreach activities Improved targeting of LPN pupils, LAC pupils and disabled pupils. Integrated approach with LSE Careers, Disability and Well-being Service, SU, EDI, Teaching and Learning, LSE Life, and academic departments Expand LSE WP student network and target support to students Collaborative work with Xxxxxxx Group and University of London networks. Build on work with black African- Caribbean pupils Review the strategic targeting of outreach work and explore expansion outside of London to further support key target groups Implement and utilise a new CRM system for communication and management of pre-entry work with participants, schools/colleges, and parents/carers. Ensure a clear pipeline of WP activity from Primary to Post-16 education with multiple interventions encouraged through regular communication with current and former participants. Advisers/teachers /schools Advising the Advisers Talks and visits to state schools Close school links Targeted admissions information and feedback for low- performing schools Evaluation As outlined in our Access Agreements from 2013 to 2016, we use evaluation feedback and data to inform our WP strategy and individual WP programmes. The LSE OFFA monitoring submission for 2014 entry contained detailed information regarding the evaluation of our access work. We also use our performance against HESA benchmarks to inform our overall direction of travel, hence the increased focus on low participation neighbourhood students since 2014. Additionally, in line with the strategic priorities in recent Access Agreement guidance, taking an evidence led approach is a key xxxxx of our Access Agreement work in 2017. Please see section 9, Monitoring and Evaluation, for more information. Collaborative working LSE has been committed to working in partnership to support our Widening Participation activity. We have developed a solid basis of collaborative work over a number of years. Examples of this in 2017 include:
Table 7. Example Phase I Outcome Payment Calculation for Group I, assuming N1=1000 Final Employment Outcome: 4.000 percentage points 4.000 percentage points < 5.000 percentage point threshold Threshold not met Final Recidivism Outcome: 191.215 bed days 191.215 bed days >= 36.800 bed day threshold Threshold met Final Transitional Job Outcome: 650 PFS Participants12 191.215 bed days >= 36.800 bed day threshold Threshold met Final Employment Outcome: 4.000 percentage points N/A = $0 Final Recidivism Outcome: 191.215 bed days 191.215 bed days * 1,000 * $85 = $16,253,275 Final Transitional Job Outcome: 650 PFS Participants 650 PFS Participants * $3,120 = $2,028,000 ESTIMATED PUBLIC SECTOR BENEFITS = $18,281,275 100% of Public Sector Benefits from Final Employment Outcome = $0 100% of Public Sector Benefits from Final Recidivism and Transitional Job Outcomes up to value of Phase I Drawdown Amount = $6,832,000 50% of Public Sector Benefits from Final Recidivism and Transitional Job Outcomes thereafter = $5,724,638 = 50% * ($16,253,275+ $2,028,000 - $6,832,000) PHASE I OUTCOME PAYMENT, capped at the Maximum Outcome Payment for Phase I ($11,095,000) = $11,095,000 (e) Release of Outcome Payment 12 Assumes that Average Hours Worked for PFS Participants that Engage in Transitional Jobs is greater than or equal to 111.
Table 7. Analysis 1: metric selection results. Metric - stressor correlation was consistent (yes) if the sign of the correlation was as expected. Xxxxxxxx rank correlation between the EQR, calculated using the formula EQR2, and the stressor is reported. A metric was redundant (redundancy=yes) if correlated (r>0.8)
Table 7. Estimated target percentages of acceptances that should have the POLAR3 flag, for the given degree subject(s). Production of these estimates is detailed in Appendix A, and was based on 2014 and 2015 data. The Actual proportions shown are based on Table 3 acceptances data for the same years, as discussed above. These estimates indicate that for Sciences and Arts subjects, reasonable targets based on the recent pool of 2014-15 applicants are that 11.5% and 9.1% of accepted students should have the POLAR3 flag, respectively. For Sciences and Arts combined (“All subjects excl. Maths”), the figure is 10.2%. The actual proportion of admissions for Arts was already very close to the Arts target in 2014 and 2015 (difference of <0.1%), although for Sciences the actual proportion was approximately 0.5% below the target. The estimate for Mathematics only was that 15.0% of accepted students should have the POLAR3 flag, whereas only 11.5% of acceptances actually did have the flag in 2014-15, but the estimate did not take into account STEP which is of critical importance for Mathematics. The target of ~10.5% produced for “All subjects incl. Maths” might be slightly affected by this, but nonetheless we decided that this target figure was the most relevant to our Access Agreement with OFFA, because it covers admissions to the collegiate University for all subjects, including Mathematics. The estimates for “All subjects” discussed in the above paragraph all used subject information in their calculation. By this, we mean that - although they apply to “All subjects” once calculated - information about degree subject was taken into account when calculating them (see Appendix A for further detail). However, if we had not had, or had not used, this information about degree subject applied for, we could nonetheless have produced a less accurate target estimate. As shown in Table 7, the less accurate estimated target (including Mathematics) would have been 11.4%. In conclusion, although there are several caveats (e.g., this does not take into account choice of A Level subject, takers of alternative Key Stage 5 (KS5) qualifications, or STEP results for Mathematics applicants), when the typical A Level attainment of successful Cambridge applicants, and the typical proportions of Cambridge applicants in each A Level attainment band with and without the POLAR flag, and the type of subject applied for are all taken into account, a reasonable admissions target for POLAR-flagged applica...
Table 7. 4 below summarises the proposed monitoring frequency and water quality parameters for the impact monitoring.
Table 7. 4.3. The limits for vehicle in configuration "RESS charging mode coupled to the power grid" with input current > 16 A and ≤ 75 A per phase and subjected to conditional connection are given in paragraph 7.4.2.2. Table 8. Annex 12 - Appendix 1 Figure 1 Vehicle in configuration "RESS charging mode coupled to the power grid" Annex 13 Method(s) of testing for emission of radiofrequency conducted disturbances on AC or DC power lines from vehicle.
Table 7. Sample ex-post interviews INFN All Management HR Gender Equality Officer Others GENERA Team Member14 F M F M F M F M F M Organizational perspective is well represented due to high number of interviewees at management level. Status GEP INFN developed no GEP within GENERA as a GEP was in place in the GENERA runtime and a new one is currently negotiated. Implementation of old GEP Thus the main aim within GENERA was to learn from other organisations and include this knowledge in ongoing activities, but also feed them into the new GEP (IP61). The GEPs are developed by the CUG (equal opportunity office) whose head was also the Implementation manager of GENERA. Thus the activities on GEP were often closely linked between CUG and GENERA. The content of the current GEP included the following measures: Mentoring Program: even though there were initial doubts about implementing it, the experiences from partners within GENERA led to its implementation within the project runtime (IP61). For raising awareness the management asked CUG to prepare a document on unconscious bias (only in Italian) which is promoted throughout the organisation, mainly in selection committees and upper organisational levels (IP63); No trainings are offered yet but they are an idea (IP61, 69). Outreach activities: Master classes were organised for women only. One masterclass was only for elementary children because “they start there to have a bias” (IP61). Due to some critical voices, a new approach could be to have mixed classes but only female tutors and to talk about gender issues. At the Gender in Physics Day, these actions in schools were presented. This format will be realised also in the future (IP64). Childcare: increased efforts (IP61). Activities and discourses in / related to GENERA Within GENERA one of the primary targets was to raise awareness, within INFN but also outside, mainly in schools in order to increase the number of girls interested in physics. You “have to start changing things there, in the mind of women and men that are working there.” (IP61) Within INFN, awareness raising happened mainly at the top management 14 All interviewees who are GENERA team members are listed here and not in another function that they might also cover,
Table 7. The means for the own personal growth as a driver M1 SD1 M2 SD2 Time of the measurement 3.65 .82 3.82 .69 Form of teaching safe driving course 3.80 .81 3.97 .64 theory lesson 3.51 .81 3.61 .71 Educational background working 3.77 .98 3.78 .71 studying 3.58 .68 3.82 .67 Age ≤ 20 3.62 .76 3.78 .65 >20 3.54 .90 4.04 .73 Gender male 3.68 .86 3.81 .71 female 3.65 .79 3.83 .66 1= first measurement 2= second measurement Table 8. Analysis of variance for Personal growth as a driver Source df F η p Measurement (M) 1 5.70 .03 .02 Form of teaching (F) 1 3.33 .02 .07 Educational background (E) 1 0.14 .00 .70 Age (A) 1 .54 .00 .46 Gender (G) 1 .04 .00 .85 F x G 1 .64 .00 .42 M x G 1 .41 .00 .52 A x G 1 .06 .00 .81 E x G 1 .21 .00 .65 M x F 1 .03 .00 .86 F x A 1 .07 .00 .79 F x E 1 .73 .00 .39 M x A 1 3.94 .02 .05 M x E 1 2.72 .02 .10 E x A 1 .01 .00 .94 error 173 p p The time of the measurement had a main effect on the experiences of personal growth (F1,173=5.70, p<.05, η 2=.03). Thus, the driving school education following the rules of coaching offered the subjects a better possibility to experience personal growth as a driver than the normal driving school education. The time of the measurement and age had an interaction on the experiences of personal growth (F1,173=3.94, p<.05, η 2=.02) (Figure 2).
Table 7. 5 below summarises the proposed monitoring frequency and water quality parameters for post project monitoring.
