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Melissa Haeffner

Utah State University - Logan; UT | NSF Post Doctoral Research Scientist

Subject Areas: social science, water, human rights, climate change

 Recent Activity

ABSTRACT:

Forty-two water decision makers in cities in Utah were identified representing elected official positions as well as staff (e.g., public utilities, public works, etc.). Three valleys in the rapidly growing Northern Utah Wasatch Range Metropolitan Area (WRMA) are represented. In smaller cities where staff play multiple roles, those who performed some operations in water management were selected. Those selected for interviews were identified through city websites and, in a few cases, phone calls to city hall. Participants were contacted by email first and followed up telephone as needed.

All of the interviews were conducted in-person between November 2015 and July 2016. During this time, city elections complicated contact and identifying key informants. When able, we interviewed the incumbents. Only one potential respondent who had initially agreed to an interview canceled without follow-up, for a response rate of 97.6%. Interviews were audio-recorded and tended to last between 20 and 90 minutes each. Each interview was transcribed with the help of two transcribers and deductively coded for themes by a team of three using NVIVO 11 Pro. The team started with an a priori coding matrix based on the interview guide and allowed for additional themes to emerge through the revision of categories and the coding agenda, reaching inter-coder reliability (<80% kappa coefficient). The database in NVIVO titled CKI_project_TEAM contains 40 transcribed interviews. One interview was not coded due to irrelevance and the pilot interview was not coded. Interview 013 does not exist because the respondent canceled. Overall, coders maintained a range of kappa coefficients with % minimum agreement. The final agreement measurements were calculated on Interview 38 which was coded by all three coders. High dual-coder agreement was also attained on the following interviews: 001, 003, 004, and 011. Coders met weekly to retain alignment in nodes and definitions (qualitative agreement). Coders were instructed to code every respondent sentence to the period (quantitative agreement). If the respondent's answer was short (e.g., Yes/No), the coder coded the interview question along with the answer to retain context. Respondents were asked the following: 1) the one key water issue facing their city today; 2) if their city had an adequate water supply to meet their city’s needs today, and 3) did they think their city had an adequate water supply to meet their city’s needs in the future.

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ABSTRACT:

iUTAH researchers contacted municipal water provider organizations in the 12 cities represented in the 2014 household survey that maintain billing records or other water use records. Of the 12, 11 cities released data under a strict confidentiality agreement outlined in a memorandum of understanding to link water bills from months in 2014 to parcels or buildings where individual survey respondents were located. The water bills were matched to results from a 2014 household survey. Researchers at Utah State University and the University of Utah implemented the ‘2014 iUTAH Household Survey’ with over 2,300 randomly selected households in 2014 in 23 neighborhoods in 12 Utah communities. The survey included detailed individual- and household-level information about water management behaviors, perceptions of water resource conditions, and attitudes toward a range of water policies and programs.

The survey research team leaders agreed to:
• Treat any water use or billing records with care and discretion and to respect the privacy rights of individual water system customers.
• Aggregate the results of our analysis so that the historic water use levels and water bills of any individual customer, building or parcel are not released in any publicly accessible document, presentation, or report.
• Never share the detailed water use records with any other individual or group without the expressed written permission of the municipal water provider organization.
• Ensure that any person who has access to the raw individual-level survey and water use datasets have completed institutional review board human subjects research training, are currently certified and authorized to work with the data, and agree to the stringent confidentiality protocols listed above.
• Not reveal the specific location or identity of individual respondents to the 2014 iUTAH Household Survey to any other individual or organization, including the partner municipal water provider organization.

The municipal water provider organization representatives agreed to:
• Provide an electronic dataset of billing or water use records that permit a reliable estimate of actual rates of water consumption at the parcel or building scale.
• Address, tax parcel, or other information that allows these records to be linked to the individual parcels, buildings, or customer addresses.
• Not require the research team to reveal to the municipal provider the identity of which specific parcels or households were either sampled into or responded to our survey.

The data cleaning process included the following steps:
a. Calculate monthly estimates
b. Calculate per capita based on household size
c. Calculate per acreage
d. Calculate tiered cost
e. Match household survey responses with water bill data

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ABSTRACT:

Forty-two water decision makers in cities in Utah were identified representing elected official positions as well as staff (e.g., public utilities, public works, etc.). Three valleys in the rapidly growing Northern Utah Wasatch Range Metropolitan Area (WRMA) are represented. In smaller cities where staff play multiple roles, those who performed some operations in water management were selected. Those selected for interviews were identified through city websites and, in a few cases, phone calls to city hall. Participants were contacted by email first and followed up telephone as needed.
All of the interviews were conducted in-person between November 2015 and July 2016. During this time, city elections complicated contact and identifying key informants. When able, we interviewed the incumbents. Only one potential respondent who had initially agreed to an interview canceled without follow-up, for a response rate of 97.6%. Interviews were audio-recorded and tended to last between 20 and 90 minutes each. Each interview was transcribed with the help of two transcribers and deductively coded for themes by a team of three using NVIVO 11 Pro. The team started with an a priori coding matrix based on the interview guide and allowed for additional themes to emerge through the revision of categories and the coding agenda, reaching inter-coder reliability (<80% kappa coefficient). The database in NVIVO titled CKI_project_TEAM contains 40 transcribed interviews. One interview was not coded due to irrelevance and the pilot interview was not coded. Interview 013 does not exist because the respondent canceled. Overall, coders maintained a range of kappa coefficients with % minimum agreement. The final agreement measurements were calculated on Interview 38 which was coded by all three coders. High dual-coder agreement was also attained on the following interviews: 001, 003, 004, and 011. Coders met weekly to retain alignment in nodes and definitions (qualitative agreement). Coders were instructed to code every respondent sentence to the period (quantitative agreement). If the respondent's answer was short (e.g., Yes/No), the coder coded the interview question along with the answer to retain context. Respondents were asked the following: 1) the one key water issue facing their city today; 2) if their city had an adequate water supply to meet their city’s needs today, and 3) did they think their city had an adequate water supply to meet their city’s needs in the future.

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Website http://www.melhaeffner.com
Resources
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Community Key Informant
Created: March 21, 2017, 8:24 p.m.
Authors: Melissa Haeffner · Courtney Flint · Douglas Jackson-Smith

ABSTRACT:

Forty-two water decision makers in cities in Utah were identified representing elected official positions as well as staff (e.g., public utilities, public works, etc.). Three valleys in the rapidly growing Northern Utah Wasatch Range Metropolitan Area (WRMA) are represented. In smaller cities where staff play multiple roles, those who performed some operations in water management were selected. Those selected for interviews were identified through city websites and, in a few cases, phone calls to city hall. Participants were contacted by email first and followed up telephone as needed.
All of the interviews were conducted in-person between November 2015 and July 2016. During this time, city elections complicated contact and identifying key informants. When able, we interviewed the incumbents. Only one potential respondent who had initially agreed to an interview canceled without follow-up, for a response rate of 97.6%. Interviews were audio-recorded and tended to last between 20 and 90 minutes each. Each interview was transcribed with the help of two transcribers and deductively coded for themes by a team of three using NVIVO 11 Pro. The team started with an a priori coding matrix based on the interview guide and allowed for additional themes to emerge through the revision of categories and the coding agenda, reaching inter-coder reliability (<80% kappa coefficient). The database in NVIVO titled CKI_project_TEAM contains 40 transcribed interviews. One interview was not coded due to irrelevance and the pilot interview was not coded. Interview 013 does not exist because the respondent canceled. Overall, coders maintained a range of kappa coefficients with % minimum agreement. The final agreement measurements were calculated on Interview 38 which was coded by all three coders. High dual-coder agreement was also attained on the following interviews: 001, 003, 004, and 011. Coders met weekly to retain alignment in nodes and definitions (qualitative agreement). Coders were instructed to code every respondent sentence to the period (quantitative agreement). If the respondent's answer was short (e.g., Yes/No), the coder coded the interview question along with the answer to retain context. Respondents were asked the following: 1) the one key water issue facing their city today; 2) if their city had an adequate water supply to meet their city’s needs today, and 3) did they think their city had an adequate water supply to meet their city’s needs in the future.

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Generic Generic
2014 Utah Cities Water Use Data
Created: March 23, 2017, 5:27 p.m.
Authors: Douglas Jackson-Smith · Melissa Haeffner · Tanner Ellison

ABSTRACT:

iUTAH researchers contacted municipal water provider organizations in the 12 cities represented in the 2014 household survey that maintain billing records or other water use records. Of the 12, 11 cities released data under a strict confidentiality agreement outlined in a memorandum of understanding to link water bills from months in 2014 to parcels or buildings where individual survey respondents were located. The water bills were matched to results from a 2014 household survey. Researchers at Utah State University and the University of Utah implemented the ‘2014 iUTAH Household Survey’ with over 2,300 randomly selected households in 2014 in 23 neighborhoods in 12 Utah communities. The survey included detailed individual- and household-level information about water management behaviors, perceptions of water resource conditions, and attitudes toward a range of water policies and programs.

The survey research team leaders agreed to:
• Treat any water use or billing records with care and discretion and to respect the privacy rights of individual water system customers.
• Aggregate the results of our analysis so that the historic water use levels and water bills of any individual customer, building or parcel are not released in any publicly accessible document, presentation, or report.
• Never share the detailed water use records with any other individual or group without the expressed written permission of the municipal water provider organization.
• Ensure that any person who has access to the raw individual-level survey and water use datasets have completed institutional review board human subjects research training, are currently certified and authorized to work with the data, and agree to the stringent confidentiality protocols listed above.
• Not reveal the specific location or identity of individual respondents to the 2014 iUTAH Household Survey to any other individual or organization, including the partner municipal water provider organization.

The municipal water provider organization representatives agreed to:
• Provide an electronic dataset of billing or water use records that permit a reliable estimate of actual rates of water consumption at the parcel or building scale.
• Address, tax parcel, or other information that allows these records to be linked to the individual parcels, buildings, or customer addresses.
• Not require the research team to reveal to the municipal provider the identity of which specific parcels or households were either sampled into or responded to our survey.

The data cleaning process included the following steps:
a. Calculate monthly estimates
b. Calculate per capita based on household size
c. Calculate per acreage
d. Calculate tiered cost
e. Match household survey responses with water bill data

Show More
Composite Resource Composite Resource

ABSTRACT:

Forty-two water decision makers in cities in Utah were identified representing elected official positions as well as staff (e.g., public utilities, public works, etc.). Three valleys in the rapidly growing Northern Utah Wasatch Range Metropolitan Area (WRMA) are represented. In smaller cities where staff play multiple roles, those who performed some operations in water management were selected. Those selected for interviews were identified through city websites and, in a few cases, phone calls to city hall. Participants were contacted by email first and followed up telephone as needed.

All of the interviews were conducted in-person between November 2015 and July 2016. During this time, city elections complicated contact and identifying key informants. When able, we interviewed the incumbents. Only one potential respondent who had initially agreed to an interview canceled without follow-up, for a response rate of 97.6%. Interviews were audio-recorded and tended to last between 20 and 90 minutes each. Each interview was transcribed with the help of two transcribers and deductively coded for themes by a team of three using NVIVO 11 Pro. The team started with an a priori coding matrix based on the interview guide and allowed for additional themes to emerge through the revision of categories and the coding agenda, reaching inter-coder reliability (<80% kappa coefficient). The database in NVIVO titled CKI_project_TEAM contains 40 transcribed interviews. One interview was not coded due to irrelevance and the pilot interview was not coded. Interview 013 does not exist because the respondent canceled. Overall, coders maintained a range of kappa coefficients with % minimum agreement. The final agreement measurements were calculated on Interview 38 which was coded by all three coders. High dual-coder agreement was also attained on the following interviews: 001, 003, 004, and 011. Coders met weekly to retain alignment in nodes and definitions (qualitative agreement). Coders were instructed to code every respondent sentence to the period (quantitative agreement). If the respondent's answer was short (e.g., Yes/No), the coder coded the interview question along with the answer to retain context. Respondents were asked the following: 1) the one key water issue facing their city today; 2) if their city had an adequate water supply to meet their city’s needs today, and 3) did they think their city had an adequate water supply to meet their city’s needs in the future.

Show More