II. INVESTIGACIÓN
5. Discusión de los resultados
I conducted four case studies to explore state-level attempts to pass paid family leave policies and identify the barriers and facilitating factors that arose, as well as the lessons that were learned through this process. My case studies used two sequential, qualitative strategies, including an in-depth content analysis and key informant interviews.
First, I completed a review of information that was publicly available in early 2016 (including Web sites, peer-reviewed publications, and other formal enactments) in order to determine state policy activity. Through this review I identified five U.S. states that had adopted a paid family leave policy at the time, including California, New Jersey, Rhode Island,
Washington, and New York. I also identified 20 states that had made legislative attempts to adopt a policy that did not end up passing (Arizona, Connecticut, Colorado, Delaware, Georgia, Hawaii, Illinois, Indiana, Kentucky, Louisiana, Maryland, Massachusetts, Minnesota, Missouri, Nebraska, Oklahoma, Utah, Vermont, Virginia, and Wisconsin). Additionally, one state (Ohio) and the District of Columbia still had active bills as of October, 2016.
42 Case Selection
I then selected four states (California, New York, Colorado, and Illinois) for in-depth case studies to better understand their respective processes, barriers, facilitating factors, and lessons learned related to their efforts to adopt a policy (Tables 4 and 5 provide state
comparisons). I chose California and New York over New Jersey and Rhode Island because of the potential applicability of their programs to other states, and because of the potential for a “control” state (Colorado for California and Illinois for New York). Washington was not selected for a case study because at that time, the state still had not determined how to implement the law that had been passed. The New York budget bill was signed on April 4, 2016 and the paid family leave program went into effect on January 1, 2018. The California law was initially enacted in 2002, and was amended and strengthened in 2013, 2016, and 2018 by additional bills. Both California and New York had ongoing efforts around paid family leave for a number of years. Colorado and Illinois had both made attempts to pass a paid family leave policy in 2015 or 2016 that did not succeed.
My intent was to analyze the efforts of these four states as separate case studies. I attempted to select states that were comparable in terms of geographic location, population size, rurality, and political and other socio-demographic factors, in an attempt to limit external factors that would influence outcomes. While all states are different, the comparison states that were unsuccessful did share many characteristics with those that were successful in passing paid family leave legislation.
I selected Colorado as a comparison state for California because the states are very similar across a number of demographic characteristics related to age, gender, race, education, income, and household (household size and median household income). California and Colorado
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are both considered “western” states, and are similar in terms of political composition. At the time of study, California had a Democratic governor, and Democrats held a majority in both chambers of the legislature. Colorado had a Democratic governor, a slight Republican majority in the Senate, and a Democratic majority in the House. However, California is much larger than Colorado, has a higher Asian population, and a higher percent of the population that identifies as Hispanic or Latino. Additionally, a higher percent of California residents were born in a country other than the U.S. and a higher percentage of the population in California speak a language other than English at home compared to Colorado.
I selected Illinois as a comparison state for New York because both states are very economically diverse, with a major metropolitan center (Chicago, IL and New York, NY–New York City is the largest city in the U.S. and Chicago is the third largest city), suburbs, and rural areas. These two states are also very similar across a number of characteristics related to age, gender, race, ethnicity, education, income, and household, and are comparable politically. At the time of study, New York had a Democratic governor, a Republican majority in the Senate, and a Democratic majority in the House. Illinois had a Republican governor and a Democratic majority in both the House and Senate. New York is larger and somewhat more diverse than Illinois, with a higher percentage of foreign-born individuals and more individuals who report speaking a language other than English at home.
Table 4: Case Study States–California and Colorado
California Colorado
State Population (2014 est.) Percent living in Urban Areas Percent living in Rural Areas
38,802,500 87% 13% 5,355,866 86% 14% Age Distribution Under 18 years 18-64 years 65 years and over
23.9% 63.6% 12.5% 23.5% 64.2% 12.3%
Gender, Female Persons 50.3% 49.8%
Racial Distribution (2013 est.) White
Black or African American
American Indian & Alaska Native Asian
Native Hawaiian & Other Pacific Isl. Two or More Races
73.5% 6.6% 1.7% 14.1% 0.5% 3.7% 88.0% 4.4% 1.6% 3.0% 0.2% 2.8% Ethnicity (2013 est.) Hispanic or Latino White Alone 38.4% 39.0% 21.0% 69.4%
Foreign born persons, 2009-2013 27.0% 9.7%
Language other than English spoken at
home, 2009-2013 43.7% 16.8%
Education (2009-2013)
High school graduate or higher Bachelor's degree or higher
81.2% 30.7%
90.2% 37% Per capita income in past 12 months,
2009-2013 (2013 dollars) $29,527 $31,109
Median Household Income (2009-2013) $61,094 $58,433
Persons below poverty level (2009-2013) 15.9% 13.2%
Date Most Recent Bill Passed/Failed 2016 (P) 2015 (F)
Date Most recent bill Implemented 2018? N/A
Previous attempts (Pass/Fail) 2002 (P), 2013 (P), 2014 (F)
Governor Jerry Brown (D, 2011–2018) John Hickenlooper (D, 2011–2018)
State Senate Majority D (26–14) R (18–17)
State House/Assembly Majority D (52–28) D (34–31)
Senate Sponsor(s) N/A Ulibarri (D)
House/Assembly Sponsor(s) Jimmy Gomez (D), Autumn R. Burke (D) Winter (D), Salazar (D)
Presidential Candidate Supported (2012) Obama Obama
Who is Eligible
Employees who participate in the State Disability Insurance (SDI) Program or a
voluntary DI plan
All employees in the state who have worked at least 680 hours in the last year
Length of Leave 6 weeks 12 weeks
Percent of Pay Currently 55%
60–70% in 2018 66% to 95% depending on earnings
Weekly Maximum $1,075 $1,000
Includes Self-care? No Yes
Includes Job Protection? No Yes
Paid for by: Employee contributions Employee contributions
Table 5: Case Study States–New York and Illinois
New York Illinois
State Population (2014 est.) Percent living in Urban Areas Percent living in Rural Areas
19,746,227 88% 12% 12,880,580 88.5% 11.5% Age Distribution Under 18 years 18-64 years 65 years and over
21.6% 64.0% 14.4% 23.5% 63% 13.5%
Gender, Female Persons 51.5% 50.9%
Racial Distribution (2013 est.) White
Black or African American
American Indian & Alaska Native Asian
Native Hawaiian & Other Pacific Isl. Two or More Races
70.9% 17.5% 1.0% 8.2% 0.1% 2.3% 77.7% 14.7% 0.6% 5.1% 0.1% 0.8% Ethnicity (2013 est.) Hispanic or Latino White Alone 18.4% 57.2% 16.5% 62.7%
Foreign born persons, 2009-2013 22.1% 13.8%
Language other than English spoken at
home, 2009-2013 29.9% 22.3%
Education (2009-2013)
High school graduate or higher Bachelor's degree or higher
85.2% 33.2%
87.3% 31.4% Per capita income in past 12 months,
2009-2013 (2013 dollars) $32,382 $29,666
Median Household Income (2009-2013) $58,003 $56,797
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Persons below poverty level (2009-2013) 15.3% 14.1%
Date Most Recent Bill Passed/Failed 2016 (P) 2016 (F)
Date Most recent bill Implemented 2018 N/A
Previous attempts (Pass/Fail) 2009 (F), 2012 (F), 2014 (F), 2015 (F) 2014 (F)
Governor Andrew Cuomo (D, 2011–2018) Bruce Rauner (R, 2015–2018)
State Senate Majority R (31–24) D (39–20)
State House/Assembly Majority D (103–42) D (71–47)
Senate Sponsor(s) Joseph Addabbo, Jr. (D) N/A
House/Assembly Sponsor(s) Catherine Nolan (D) Flowers (D)
2012 Presidential Election Obama Obama
Who is Eligible All employees in the state
Employees of businesses with 50 or more employees; state and local government
employees
Length of Leave 8 weeks in 2018
12 weeks in 2021 6 weeks
Percent of Pay 50% in 2018
67% in 2021 N/A
Weekly Maximum 50% of statewide avg. weekly wage*
(67% in 2021)
$300 for F/T employees prorated amount for P/T employees
Includes Self-care? Yes No
Includes Job Protection: Yes Yes
Paid for by: Employee contributions Employee contributions
* Benefits were phased-in beginning in 2018 for 8 weeks at 50% of the employee’s average weekly wage (AWW), capped at 50% of the statewide average weekly wage (SAWW), increasing to 12 weeks at 67% of the employees AWW, capped at 67% of the SAWW in 2021.
48 Conceptual Framework
I used the theoretical models and frameworks outlined above to study the similarities and differences between states that have tried to pass a paid family leave policy and failed, and states that succeeded. I employed Kingdon’s multiple streams theory to understand why the issue of paid family leave was included in the legislative agenda in each state, and what factors specific to the problem, policy, and politics streams influenced the outcome of each bill. I used
Mintrom’s and Paul-Shaheen’s findings about policy entrepreneurs to understand the role of influential political actors in promoting policy innovations and energizing the diffusion process, and to look at the perspectives and activities of significant interest groups and stakeholders.
Figure 3: Paid Family Leave Conceptual Framework6
6 Modified from Kingdon’s Multiple Streams Model, usingMintrom’s and Paul-Shaheen’s findings regarding policy entrepreneurs.
49 Research Questions
My study was designed to answer the following research questions:
• What factor(s) contributed to the successful passage of paid family leave policies in states that passed legislation, and what was the relative importance of each factor? (Ranging from “not important” to “critical”).
• What factor(s) contributed to the defeat of paid family leave policies in states that introduced, but did not enact legislation, and what was the relative importance of each factor? (Ranging from “not important” to “critical”).
• What lessons were learned that can help states interested in successfully enacting paid family leave policies?
Data Collection Content Analysis
For each state case study, I obtained detailed information using two qualitative strategies: in-depth content analysis and key informant interviews. I conducted my content analysis between August 2016 and May 2017, and this included two parts. Part one was a systematic review of the bills proposed in each state, bill actions and amendments, and testimony, transcripts, recordings of debates, committee and floor votes, if applicable. I conducted this review using each state’s legislative website and LegiScan, a real-time legislative tracking service that provides
monitoring of every bill in the 50 states and Congress.7 Part two was a systematic review of
7https://legiscan.com/.
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news articles, op-ed pieces, and pieces from influential columnists written about each bill from the top three daily newspapers in each state based on circulation (as well as the Denver Business Journal in Colorado). I conducted both systematic reviews using the search terms outlined in Table 6, as well as the specific bill numbers and names (if applicable).
Table 6: Bill and Newspaper Article Search Terms
At the time I conducted the content analysis, legislators in New York had introduced 24 paid family leave bills and legislators in Illinois had introduced 7 bills. Legislators in California had introduced six bills, which was later expanded to eight to include two bills introduced in 2018. Likewise, Colorado had introduced three bills, which was later expanded to four to include one additional bill introduced in 2018 (Appendix D).
I gathered news articles starting from the date one year before the bill was introduced to two weeks after the bill either passed or died. A total of 660 articles were included for initial review from 13 newspapers. I then reviewed the articles for relevance, and limited further review to pieces that focused specifically on the state paid family leave policy. For example, articles were included if they discussed the bill under consideration in the state, arguments for or against the policy, barriers and/or facilitating factors to passing or adopting the policy, sponsors,
supporters, or opponents. Articles were excluded if they discussed national level politics or
Paid AND Family AND Leave AND Policy
OR Parental OR Caregiver OR Maternity OR Paternity OR Legislation OR Bill OR Law
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policies, paid family leave policies passed in other countries, or just mentioned the idea of paid family leave without providing substantive content.
Of the 660 articles that I reviewed, I found that 115 were relevant and provided
information about the paid family leave policies under consideration in the selected states. This included 30 articles from California newspapers (Los Angeles Times, San Jose Mercury Times, and Sacramento Bee), 60 articles from New York newspapers (Wall Street Journal, New York Times, and Daily News), three articles from Illinois newspapers (Chicago Tribune, Chicago Sun-
Times, Chicago Daily Herald, and 22 articles from Colorado newspapers (Denver Post, The Gazette, The Pueblo Chieftain, and Denver Business Journal). Because a search of the Colorado Gazette did not yield any articles, and a search of the Pueblo Chieftain only provided one
relevant article, I performed a google search which led to a number of publications in the Denver Business Journal, 10 of which were relevant and subsequently included. Likewise, newspapers in Illinois did not yield many articles about House Bill 166 (three articles between all three papers), but a google search did not uncover any additional articles (Appendix E).
Key Informant Interviews
Key informant interviews are in-depth, semi-structured interviews with individuals who are knowledgeable about a specific topic and can articulate that knowledge (Patton, 2002). Following the content analysis, I conducted key informant interviews with 20 total respondents (4–6 respondents from each of the four states), including bill sponsors, legislative staff,
committee members and staff, opponents, experts, and advocates that were identified while conducting the content analysis for each state. I initially recruited subjects by email, with follow-
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up done by phone. I developed an excel spreadsheet to keep track of my efforts to recruit participants. The resulting study participants were interviewed using a common interview guide (Appendix F).
I structured my interview questions around important concepts that I drew from the existing literature related to state Health-related policy adoption and my findings from the content analysis for each state, and I organized my interview guide according to my conceptual framework provided above. I asked respondents to think broadly about efforts to pass a paid family leave policy in their state, as well as efforts to pass the most significant bill in each state (SB 1661 in CA, S 6404/A 9006 in NY, HB 166 in IL, and SB 14-196 and SB 15-1258 in Colorado).
I asked respondents to recall (to the best of their knowledge) key challenges, barriers, or facilitating factors related to efforts in the state to adopt the policy or policies. I also asked respondents about the existence or lack of an open policy window, and the existence or lack of policy entrepreneurs (political actors). Interviews with key informants helped provide a more robust picture of activities and events that took place, and major challenges and facilitating factors that led to either the passage or failure of the bill. I used open-ended questions to allow for flexibility and greater interaction with participants, and to ensure that each participant was able to provide all information that they believed to be important to my study. I also pilot-tested the interview questions prior to recruiting key informants to ensure that the questions made sense, followed a logical order, and that the interview did not take more than 45 minutes to complete.
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I conducted all of my key informant interviews by phone, using an iPhone 7 on speaker phone, recorded the interviews with the GarageBand program for Mac8 using the
“Voice/Narration Vocal” setting, and compiled field notes during each interview. Interviews were recorded as “AIFF” (Audio Interchange File Format) files, then converted to MP3 files to allow for compression (AIFF does not do compression while MP3 does) which made it easier to share the files for transcription (MP3 files are smaller than AIFF files). I did not use names or other types of identifiable information during the interviews, and in all files, I assigned each participant a numeric identifier so that their interview was not identified by name. I stored all interview recordings in password-protected files on my computer, in my office, and sent the transcripts for transcription through a secure, password-protected process. The recorded
interviews were transcribed by a transcription service,9 then I verified each transcript against the audio recording and my field notes to ensure that the transcriptions were complete and accurate.
Analysis
While analyzing the data that was collected through the content analysis and interview, my goal was to develop a complete picture of what happened in each state as they worked toward passing a paid family leave policy. I also wanted to better understand what role each of the factors outlined above (the problems that paid family leave would address, the strength of the policy idea itself, the political context, the external or environmental context, the actors, and the policy window) played in whether each state succeeded or failed.
8https://www.apple.com/mac/garageband/ 9 TranscribeMe: https://www.transcribeme.com/
54 Content Analysis
First, I reviewed all of the paid family leave bills that were proposed in each state for specific content, including: eligibility requirements, length of leave, amount of compensation (percent of pay, weekly maximum if provided), whether or not the bill included paid leave for self-care, whether or not the bill included job protection, and how the program would be funded. I also reviewed the bill’s history, including actions and amendments, any recordings or
transcripts of hearings/testimony or debates that were available, and any committee or floor votes that were recorded. All of this information was recorded in an excel file, and relevant
information can be found in Appendices G–J.
Next, I conducted a preliminary analysis of the newspaper articles that were most relevant to the paid family leave policy of interest in each state (SB 1661 in California,
A9006/S6406 in New York, HB 15-1258 in Colorado, and HB 166 in Illinois). This preliminary analysis was done using a combination of qualitative analysis software (NVivo 11) and hand coding in order to identify themes and patterns. I used this information along with the
information that I derived from the literature and conceptual models outlined above to develop a draft code book. I then conducted a second analysis of all of the news articles using the code book, added additional sub-codes that emerged during this process, and I revised my draft code book based on these additional codes (my final code book is provided in Appendix K).
I conducted my content analysis first, which helped me identify key messages in support of or in opposition to the bills, challenges, barriers, and facilitating factors, and the existence or lack of policy entrepreneurs (political actors) in each state. Findings from my content analysis also helped inform the questions that I asked during my key informant interviews.
55 Key Informant Interviews
All interviews were recorded, so during each interview I wrote field notes on paper interview guides about key themes that emerged. Once I had transcriptions of each recording and had verified that they were accurate, I followed Creswell’s eight steps for coding qualitative data (Creswell, 2014):
1. Read all transcriptions carefully to get a sense of the whole;
2. Go through several of the documents thoroughly, think about the underlying meaning; 3. Make a list of all topics, clustering similar topics;
4. Take this list and apply it to your data. Use this as a preliminary organizing scheme, see if new categories and codes emerge;
5. Turn your topics into categories (with descriptive wording), group related topics; 6. Decide on an abbreviation for each category and alphabetize the codes;
7. Perform a preliminary analysis;