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6. Assess project attribution The use of specific participatory methods to assess attribution is discussed below, but in general the preferred approach is to separate the project and non-project causative factors, and to find the relative importance of these factors in the explanation of an identified positive or negative outcome or impact. PIA methods can also be used to assess attribution when using ‘matching methods’. 7. Triangulate Triangulation is essential for all data collection methods, including participatory methods. Sometimes secondary data can be used to check if estimates are in the right ‘ball park’; a short household survey could be implemented to check participatory methods; or different participatory methods can be used for triangulation purposes. 8. Feedback and verity the results with the community It is essential to feed the analysis back and to discuss the results with the communities and other stakeholders. This is the last opportunity to ‘ground truth’ the results, and the discussions usually reveal further insights into project outcome and impact processes. Focus groups, e.g., by gender, are advisable for getting the best feedback quality. Description of PIA data collection methods (and examples) Simple ranking and scoring methods A simple initial approach is to rank and/or score the importance of different possible contributory factors for a given impact or outcome by placing counters (e.g., seeds or stones) on each potential contributory factor - these should be represented as far as possible by a picture card or other visual aid, ideally using local materials. The ‘proportional piling’ technique involves distributing 20, 50 or 100 stones or seeds among a number of variables (e.g., contributory factors, potential impacts or indicators). It should be noted that the greater is the number of counters, the longer the exercise takes – fewer counters can be used if there are less variables or indicators. The results of proportional piling can be conveniently presented in a pie chart, as shown in Figure T14. Ranking can also be undertaken through a voting process using a secret ballot to reduce the bias caused by peer pressures, strong personalities, etc. Ranking and scoring should be undertaken by different focus groups, e.g., women and men, and then aggregated. ‘Before and after’ scoring including the use of ‘nominal baselines’ ‘Before and after’ scoring involves undertaking proportional piling for the ‘before project’ situation for a particular variable or indicator (e.g., the pre-project annual cash value of forest products), and asking the informants or focus group to increase or remove counters according to whether they think the annual cash value has increased or fallen since the project started compared to the present Social Impact Assessment of Land-Based Carbon Projects (1.0) – Part II | 47
day. The ‘before project’ score provides the baseline or starting index. Before and after scoring can also be useful if a community outcome or impact is in terms of the time saved on key household activities, e.g., collection of water, fodder or firewood. In many cases, people are unwilling to reveal certain types of information, especially financial information such as income levels, and even discussing production levels can be sensitive. Income data based on surveys and conventional participatory methods should be treated with extreme caution since they are likely to suffer from major bias problems 9 . Figure T15 presents an example of ‘before and after’ scoring for a hypothetical community vegetable garden project. It is essential that the reasons for any differences in the before and after scores are thoroughly discussed and recorded. 9 In general it is more reliable to measure wealth as a proxy for income (TRANSLINKS, 2007). Social Impact Assessment of Land-Based Carbon Projects (1.0) – Part II | 48
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MANUAL FOR SOCIAL IMPACT ASSESSMENT
Page 3 and 4:
Table of Contents T1 Introduction t
Page 5 and 6: List of Boxes Box T1. General Data
Page 7 and 8: Forest Trends’ mission is to main
Page 9 and 10: List of Acronyms (Core Guidance and
Page 11 and 12: Sections T5 and T6 present a range
Page 13 and 14: Figure T1: The Main Stages and Step
Page 15 and 16: Figure T2: Example of a Conceptual
Page 17 and 18: Figure T4: Generic Conceptual Model
Page 19 and 20: Stages 3-5 of Open Standards The re
Page 21 and 22: Figure T7: Diagram of the ROtI Anal
Page 23 and 24: table so they can be read, discusse
Page 25 and 26: Table T1: Theory of Change for Seyc
Page 27 and 28: T2.4 Participatory Impact Pathways
Page 29 and 30: Table T4: The PIPA Outcomes Logic M
Page 31 and 32: Main Sources and Further Guidance h
Page 33 and 34: T3 Sustainability Framework Approac
Page 35 and 36: Figure T12: SAPA Initiative Modifie
Page 37 and 38: 1. Identify a small group of key in
Page 39 and 40: Table T6: Example of LOAM Livelihoo
Page 41 and 42: T4 Matching Methods T4.1 Introducti
Page 43 and 44: Advantages and Disadvantages of ‘
Page 45 and 46: Box T1. General Data Collection and
Page 47 and 48: Box T3. Data Collection Methods Pro
Page 49 and 50: T6 Specific Data Collection Methods
Page 51 and 52: Table T8: Example of a Household BN
Page 53 and 54: The poverty index can range from 0%
Page 55: The PIA guide proposes the followin
Page 59 and 60: Figure T15: “Before and After”
Page 61 and 62: Table T10: Pair-Wise Ranking Showin
Page 63 and 64: Impact calendars Impact calendars c
Page 65 and 66: A large sample is needed to be conf
Page 67 and 68: Table T15: Scoring of Changes in Ag
Page 69 and 70: Table T17: QPA Scoring of Social Eq
Page 71 and 72: T6.4 Participatory Economic Valuati
Page 73 and 74: Advantages and Disadvantages of Par
Page 75 and 76: The stories are collected from thos
Page 77 and 78: Main Sources and Further Guidance D
Page 79 and 80: Table T19: Stakeholder Analysis Pro
Page 81 and 82: Figure T18. Venn Diagram with Stake
Page 83 and 84: T7.2 Problem Trees Assuming it is p
Page 85 and 86: T7.3 Scenario Analysis Scenarios ar
Page 87 and 88: Box T7. Driving Forces in a Communi
Page 89 and 90: Maack, J.N. 2001. Scenario analysis
Page 91 and 92: In terms of non-monetary benefits,
Page 93 and 94: and duration of employment, the sta
Page 95 and 96: Physical Capital Positive changes i
Page 97 and 98: these strategic resource off-limits
Page 99 and 100: einforce existing institutions or n
Page 101 and 102: PROJECT: PROFAFOR TYPE: Plantations
Page 103 and 104: their occurrence will depend in lar
Page 105 and 106: HUMAN CAPITAL Increase in perceptio
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Table T26: Potential Mid- to Long-T
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Figure T20: Example of Relationship
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Figure T22: Additional Potential So
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T9 Further Guidance on Indicator Se
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Box T9. Goals and Indicators Defini
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When selecting indicators, it is be
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Table T27: Indicator Quality Assess
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Box T10. Indicators Derived from th
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T9.5 Disaggregating Indicators Mult
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Mayoux, L. 2001. What Do We Want to
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Landscape Outcomes Assessment Metho
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• Access to essential services (w
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T10.3 Social Indicators Derived fro
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Empowerment of women indicators:
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CCBA, 2008. Climate, Community & Bi
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James A., Pangtey V., Singh P. & Vi
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SEEP Network. 2006. Social Performa
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