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Consultancy For Quantitative Data Collection To Assess Digital Extension And Advisory Services In Kenya

Closing: Jun 10, 2022

16 days remaining

Published: May 13, 2022 (12 days ago)

Job Requirements

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Job Summary

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Required Qualifications

  • Demonstrated experience conducting quantitative survey fieldwork in Kenya within the past 5 years.
  • Demonstrated experience conducting survey-related trainings.
  • Expert knowledge of local content and languages in the target areas.
  • Experience in building trust and good relations with village leaders, interviewees, and communities.
  • Strong program management skills.
  • Demonstrated experience in successfully coordinating large field teams and managing deliverables.
  • Excellent computer skills and experience using CAPI and statistical software packages.


Responsibilities

Required Qualifications

  • Demonstrated experience conducting quantitative survey fieldwork in Kenya within the past 5 years.
  • Demonstrated experience conducting survey-related trainings.
  • Expert knowledge of local content and languages in the target areas.
  • Experience in building trust and good relations with village leaders, interviewees, and communities.
  • Strong program management skills.
  • Demonstrated experience in successfully coordinating large field teams and managing deliverables.
  • Excellent computer skills and experience using CAPI and statistical software packages.


The selected firm will be expected to carry out the following tasks:

  • Translate survey instrument and interview guide into local languages (as needed).
  • Obtain local ethical clearance for the quantitative survey fieldwork.
  • Obtain a sufficient number of tablets for CAPI data collection.
  • Develop, test, and finalize the CAPI data entry program that will be used to conduct the interviews in the field.
  • With assistance from the IFPRI, prepare the field implementation manual prior to enumerator training. The field manual will be the basis for quality assurance of the data collection process.
  • Organize the selection, hiring, and payment of enumerators to conduct the required data collection work. This will include hiring both male and female interviewers with the necessary language skills to ensure respondents for the individual interviews are matched on sex.
  • Facilitate and ensure the smooth operation of the enumerator training and survey pretest in collaboration with IFPRI staff. IFPRI and the selected firm will jointly consider the COVID-19 implications of whether IFPRI staff conducting the training will do so in-person or virtually. It is expected that there will be a 5-day training, followed by a 2-day pretest and debrief, for the quantitative survey.
  • Develop a field schedule for the quantitative data collection teams and provide regular status updates during fieldwork.
  • Develop spot- and back-check protocols and share these with IFPRI for feedback prior to the start of data collection.
  • Participate in weekly meetings with IFPRI throughout data collection.
  • Share the data generated from the spot and back-checks and additional data collection concerns with IFPRI in a timely manner so that issues can be promptly resolved.
  • Share the data generated from CAPI (in Stata format) with IFPRI during data collection, as and when the data is uploaded to the servers. These data will not be the cleaned data sets (except for variable and value labels, checking and correcting skip patterns, formatting the data in long format as required), but the raw data sets as sent to the firm from their survey teams.
  • Conduct data cleaning to ensure consistency and range-checks; share the error check do-files with IFPRI.
  • Provide responses to queries from IFPRI in relation to data cleaning (as needed).
  • Deliver cleaned data sets (in Stata format) from the 1000 households in long format. The dataset should include translation of any open-ended questions from local languages to English if necessary.
  • Provide a short report covering quantitative survey fieldwork, as well as any issues related to data management and cleaning.


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