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Publication: Journal of Legal, Ethical and Regulatory Issues
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Pressure to produce better and more efficient schools has been felt by education policymakers across all levels. By statute, providing a system of public education rests with state legislatures, and lawmakers have become more assertive in directing policy to improve schools. McDonnell (2001) confirms the increasing role governors and legislators have taken in directing state education policy over the past several years. She asserts the role of education specialists including chief state school officers has declined. The extent of legislative involvement in education policymaking is confirmed by Fowler (2009) who writes, "State government has become increasingly important in the last 25 years and will probably continue to do so" (p. xii).

Despite the ongoing interest by state lawmakers to produce education policy, few professional educators have a clear understanding of how public will is transformed into public policy (Fowler, 2009). Moreover, why politicians make decisions on whether to vote for or against a particular bill is ambiguous. Building upon a previous qualitative study (Canfield-Davis, 1996) conducted with 25 legislators, the purpose of this descriptive study was to examine the numerical ranking of the factors of influence that shape legislative decision-making.

Using a behavioral research model (Wahlke and Eulau, 1959) Canfleld-Davis (1996) discovered 18 key factors of influence that shape legislative decision making. Fiscal impact, trust, constituents, timing of when a bill is introduced, committee chairs, legislative leadership, sources of information, sponsor, regionalism, governor, interest groups, lobbyists, sources of voting advice, re-election, state agency bureaucrats/civil servants, religion, legislative staff, and media were among the 18 key factors found. The present study provides a numerical ranking in order from high to low of these 18 factors.


Policy decisions in state legislatures may be influenced by any number of sources known to shape human behavior (Patterson, 1983). Wirt, Morey, and Brakeman (1970) identified the three variables affecting voting behavior as: (a) personal characteristics or affiliations including political party, age, gender, socioeconomic background, seniority and committee membership; (b) the home district of the legislator; and (c) the type of constituency represented in terms of urban-rural, agricultural-industrial, ethnic-religious, and affluent versus poor. Patterson identified six sources of influence including: (a) party and party leaders, (b) committees, (c) staff, (d) lobbyists, (e) the governor, and (f) a legislator's constituents.

To pinpoint the factors of influence upon legislative decision-making, researchers have observed the norms governing legislators' behavior, the roles they assume, and the goals and objectives that motivate them (Clausen, 1994). Analyzing the possible influences upon lawmakers' voting decisions is complex. Patterson (1983) noted multiple confounding influences are present in legislative decision-making. Interest groups, governors, party affiliation, and legislative committees were among some.

Despite these challenges of complexity, studies focusing upon influence variables pertaining to state legislative decision-making have been conducted. In a study of the effectiveness of statelevel education lobbying strategies in Minnesota, Mazzoni, Sullivan, and Sullivan (1983) asked legislators to identify what factors influenced their education policy decisions. Legislators give weight to personal feelings, constituent desires, recommendations of colleagues, staff recommendations, interest groups views, and recommendations of friends when making decisions about school issues.

Keese (1990) devised three cluster rankings to categorize the sources of influence perceived by Tennessee legislators as effective and reliable. She found fellow legislators and education lobbyists to be the most effective and reliable sources of influence for decision-making. Local school administrators, special interest groups, family and friends, business and industry lobbyists, teachers, state agencies, and constituents fell into the medium ranee of effectiveness for decision-making. The least important sources of influence on legislative decisions were party, parents, national and regional organizations, legislative staff, college or university representatives, and the governor. Flagel (1990) looked at various individual and group factors influencing voting behavior on school finance reform policy decisions in Texas. In terms of individual factors, Flagel determined running for re-election had the strongest influence on voting decisions. Tenure and previous voting record had a moderate influence, and gender and age did not affect decisions. Group factors with a strong influence on legislative voting behavior included party affiliation and wealth of the legislator's home district.

Roberson, Durtan, and Barnham (1992) studied selected influences on the voting decisions of the Virginia General Assembly. They found legislators ranked their personal views as having the strongest influence on their voting behavior followed by constituents, interest groups and colleagues in the legislature next, and staff last. According to a study of the decision-making process conducted by Winton-Glisson (2006) Oklahoma state legislators are, "greatly influenced by local school administrators, teachers, and other school personnel... extremely influenced by lobbyists... and heavily influenced by fellow legislators or other governmental officials" (p. 118). In an earlier analysis of New York state legislative decision making Hogan (2003) identified constituents as a major factor affecting how legislators voted on an aid bill for higher education.

In addition to the present study, several others (Hirschi, 1969; Turner, 1976) examined sources of influence upon Idaho legislators. Huckshorn (1965) wanted to know what factors as perceived by Idaho state legislators affected their voting decisions. Based upon interviews conducted with 96 of the 103 members of the legislature, Huckshorn concluded that decisions are influenced by contacts with fellow legislators, interest groups, constituents, the governor, and political parties. Respondents suggested that decisions were heavily influenced by fellow members with demonstrated expertise in a particular area of knowledge. However, no experts were identified in the field of education.

Hirschi (1969) investigated selected variables associated with personal characteristics and affiliations to determine if a relationship with voting behavior existed. He concluded legislators most likely to support education-related legislation would: (a) be older and have more legislative experience; (b) be actively involved in school -related activities; (c) represent a large population of school-aged youngsters from rural districts; (d) express religious affiliation, except those belonging to the Catholic faith; (e) be employed as a professional, semiprofessional, or a salesman; and (f) serve on a major legislative committee, but not in a leadership position.

Turner (1976) identified 20 interest groups perceived by Idaho legislators as sources of influence on decisions regarding selected education bills. She found legislators most frequently contacted their colleagues in the legislature for information about education legislation. Lawmakers also sought advice and information from school administrators, the State Board of Education, and individual citizens. Although professional educational associations ranked first as reliable sources of information, lawmakers did not frequently contact them. Legislators ranked school trustees second and administrators third as reliable information sources.

Exploration of the influence variables on legislative decision-making is convoluted. Some of the factors that have been shown to influence voting behavior include age, gender, socioeconomic background, religion, legislative seniority, committee membership, party affiliation, staff interest groups, lobbyists, legislators' constituents, and personal views and values. This study builds upon previous research conducted on legislative decision-making, and attempts to determine the degree to which 18 key factors of influence swayed voting decisions.


During the 2009 legislative session, 105 surveys were mailed to the total population of legislators in a northwestern state. The surveys were accompanied by a cover letter introducing the researchers, outlining the purpose of the study, and ensuring confidentiality of responses. Also included was a description of 1 8 variables and an identical stamped envelope to return the completed survey. Anonymity was further ensured by leaving the surveys unmarked Due to the size of this particular legislature, individual legislators are not assigned legislative aides. Therefore, it was assumed by the researchers, legislators personally completed the surveys.

Legislators consisted of 76 % Republicans and 24% Democrats; 25% female and 75% male. Of these, 58 (55%) respondents completed the survey. The participants were comprised of 11 (19%) democrats, and 46 (79.3%) republicans, and one (1.7%) participant did not indicate party affiliation. The participants included 45 (77.6%) males and 13 (22.4%) females. The mean length of service in the legislature was 6.84 years (SD = 6.73, range = 0-42) for the 56 (96.55%) participants who indicated the years of service in the legislature.

The instrument, located in Appendix A, contained a total of 18 factors of influence listed in alphabetical order. These factors were generated based upon findings obtained from an earlier case study on the legislative process and factors of influence upon voting decisions conducted in the same state (Canfield-Davis, 1996). The survey resembled a Likert-type inventory where participants indicated the degree to which each variable influenced their voting behavior. In scoring the ordinal data collected from the surveys, consecutive integers were assigned to seven response options, with a score of 1 equating to no influence and a score of 7 as high influence. The total number of responses for each factor was calculated, and then a mean score was obtained for each. The minimum possible score on this instrument is 18 and maximum score is 126. Data gathered by the three other questions (i.e., party affiliation, gender, and the length of service in the legislature) were provided in the participant demographic section. In this study, the overall alpha reliability coefficient for the instrument was 0.81, which well exceeds Nunnally 's (1978) minimum criteria of at least 0.70 to demonstrate internal consistency. Based on reliability standards set by Springer, Abell, and Nugent (2002), the reliability for this scale is "very good".

Collected data were organized in SPSS 13 statistical software for analysis. Descriptive statistics were utilized to summarize, organize, and simplify the data (Gravetter, & Wallnau, 1996).


Results of the data analysis examining relative influence of the 18 factors determining legislative outcome is provided in Tablel. Factors are listed in rank order of highest influence to least influence.


Findings of this study show fiscal impact carried the most weight upon legislative policy decisions, and media as having the least influence. Further discussion of each variable follows.

Fiscal impact refers to the amount of money required to implement the proposed legislation, and the monetary impact on legislators' constituents. With headlines UkQ9 Massive U.S. debtforecast (Montgomery, 2009) it is little wonder lawmakers ranked fiscal impact as being the factor of influence most affecting whether legislators vote yes or no on a bill (5.83).

Trust provides the foundation upon which many other factors of influence depend. Legislators develop a network of individuals whom they trust both inside and outside the legislature. Individuals who are trusted, respected, and considered to be credible are depended upon by legislators for information and voting advice. In this study, participants ranked trust as the second factor of influence with a mean of 5.71.

Legislators represent citizens or constituents who reside in their home districts. Constituents received a mean of 5.5 1, placing it in the top three factors of influence on decision-making. Selberg (2004) expressed surprise at how low constituency ranked in her study of voting behavior on educati on funding bills in Arizona, despite prior research placing it higher. According to Ray (1982), less professional legislatures may rely on the wishes of their constituents for voting cues. The legislators surveyed for this research were members of a citizen legislature, meaning lawmakers have careers in their home districts. They are not considered professional, full time politicians and therefore, may be strongly influenced by their constituents.

Timing refers to the length of time legislators have to consider the pros and cons of proposed legislation. The mean score of the participants' response on this influence factor was 4.60. Longterm exposure to legislation increases the probability of its passage (Canfield-Davis & Jain 2009). Lawmakers in this study explained the time of a bill's formal introduction could be predictor of passage or failure, although contradictory opinions were given. Some legislators believed legislation introduced early in the session risk undergoing too many changes and revisions, causing the bill to ultimately fail.

A chairman, or co-chairmen preside over all legislative committees. This study shows committee chairmen wield a fairly high level of influence with a 4.59 mean. This finding is supported by Weaver and Geske (1997) who found current chairs and co-chairs as being highly influential in the Louisiana state legislature. Selberg (2004) confirmed chairpersons as exerting influence on legislative decision-making decisions.

For the purpose of this study, legislative leaders included the Speaker of the House, the Senate Pro Tern, and the minority leaders in both the House and Senate. A mean of 4.55 was obtained on this influence factor. Studies conducted by Milstein and Jennings (1973), Patterson (1983), Mitchell (1981), Kingdon (1997), Selberg (2004) are consistent with results of this study, indicating party leaders influence decision-making to some degree.

Legislators seek and receive information from sources beyond those who give expert testimony during committee meetings, information meetings, floor debate, and other gatherings. Information may also include written material provided from a variety of individuals and organizations. Sources of Information received a mean score of 4.47. Although this study did not focus on specific information sources, Weaver and Geske (1997) considered five sources of information to be influential in decision making: 1) the legislature; 2) legislative staff; 3) state government agencies; 4) interest groups; and 5) constituency. After identifying eight sources of information Riffe (1988) concluded that although some sources provide useful information, most are of little value when it comes to making a decision.

Bill sponsors are legislators who promote and carry bills through the legislative process. Those who are perceived to be credible, and who have the respect of their colleagues sway legislative voting decisions. This study suggests sponsors have some degree of influence with a 4.2 1 mean.

On some issues, it is not uncommon for lawmakers to align regionally in their voting patterns. In this study regionalism fell in the middle of the 18 factors of influence with a 3.93 mean. Referring to the state in which this data was collected, Stapilus (1994) points out:

But [this state] is made up of many little worlds, a surprising number for our population, split off from each other by Chinese walls. What may be common knowledge, or a topic of intense, in one area, may be little-noted in others, and even within those worlds, much is cloudy and uncertain, (p. 1)

This parochialism may guide decisions on issues that do not have statewide impact. As a factor of influence in the present study the governor obtained a 3.86 mean score, showing participants in this study had mixed reactions regarding the level of influence rendered. In the state where the data was collected, the governor was a member of the majority party. This finding supports the research conducted by Ray (1982) who found the governor's office had minimal influence despite the fact the governor belonged to the majority party. When asked what one governor did to influence legislator's voting behavior, the response was:

Basically, I know the personalities of most of the legislators to where I know where they're going to be on given issues. And that just comes with the experience of being here a long time, and knowing the people who come and go. . . And then to influence, I know basically on both sides of the House [legislature] where the votes are going to be. . .then I turn [my legislative liaison] loose and I visit with some of my friends on both sides of the aisle and ask them how many votes they can get and what I have to do. (Canfield-Davis, 1996, p. 87).

The governor' s influence on whether bills pass or fail is further illustrated by Johnson (1 9931994) who described options governors have in either approving or disapproving legislation.

As reported in Fowler (2009) an interest group is "an association of individuals or organizations . . . that, on the basis of one or more shared concerns, attempts to influence public policy in its favor" (Thomas & Hrebenar, 2004, p. 102). Examples might include teachers unions, business associations, power companies, conservation leagues, the AFL-CIO, and religious or ethnic based interest groups. Interest groups in this study ranked below the midpoint, garnering a 3 .72 mean. This may be contrary to a national trend which shows interest groups and their activities have grown in recent years, especially at the state level (Fowler, 2009). In a study of interest groups and education policy in Spain, Bonal (2000) described how the State's immediate responses to educational conflicts weakened the ability of interest groups to effectively participate or influence the decisionmaking process. The present ranking of interest groups in this study aligns most closely with that of Kingdon' s (1 997) research indicating they were neither the least or most influential on a member of Congress' vote.

Lobbyists are individuals who represent outside organizations and who provide information on proposed legislation. They are among the most astute, experienced, and knowledgeable actors in legislative policymaking (Hall & Deardorff, 2006). Ainsworth (1993) analyzed how legislators structured their interactions with lobbyists to minimize their influence. Among other findings, he concluded one of the more important roles of a lobbyist is to communicate issue relevance. In the state where the data were collected more than 400 individuals, representing multiple organizations are registered as lobbyists. With a 3.64 mean score, they rank slightly below Interest Groups.

Legislators seek voting advice from a variety of individuals largely dependent upon the issue. For example on education related issues, in addition to committee members and fellow lawmakers, legislators sought voting advice from school superintendents, teachers, lobbyists, and school board members. These researchers also found legislators depend upon each other for voting advice. A mean score of 3.55, places this factor of influence lower than a majority of other determinants on voting behavior.

Re-election is a factor of influence for legislators who want to be re-elected, or reside in a "swing" district. The mean score of 3. 16 may be attributed to the fact the majority of legislators in the state where data were obtained represent one political party, and feel confident they will return to the legislature. In the words of one former state Senator, D. Davis "No one wants to admit they cast a vote based upon their desire to be reelected" (D. Davis, personal communication, March 20, 2009). Bishin (2000) cites research conducted by Kukinski (1978) showing senators in the United States Congress who are running to be reelected are more responsive to their constituency. Despite these findings, re-election ranked lower than other factors of influence.

Examples of state agency bureaucrats include the Secretary of State, Attorney General, State Superintendent of Public Instruction, and Director of Department of Corrections. The mean score of 3.10 illustrates individuals in these positions have little influence in legislative decision making. There is irony in this phenomenon, because all of the elected bureaucrats in the state where the data was collected were members of the same dominant political party. In addition the appointed bureaucrats were selected by the Governor, who is also a member of the dominant party.

Religion refers to one' s philosophical beliefs and value systems, and in this study it received a mean score of 3.00. This number corresponds with Cann's (2009) results from an empirical test indicating personal religious identification, at least among Mormons has little influence on legislative voting. Greenawalt (1994) concurred noting that most political leaders avoid religious discourse when considering policy issues, even if their spiritual convictions may intertwine with those issues. Religious affiliation, in this study, does not appear to influence the decision-making of legislators to a high degree.

With the exception of Media, Legislative Staff received the lowest ranking as a factor of influence (mean 1.47). These individuals include members of the Legislative Services Office, and other support staff. One reason for the low ranking in this study could be attributed to the limited number of staff available in this particular legislature. However, this is consistent with Kingdon (1997) who writes, "In short, if staff are important in voting decisions, their influence is either extremely subtle or is restricted? (p. 204).

Media, including television, radio, and newspapers, received the lowest ranking for shaping legislative decisions with a mean score of 1 .05. A study of Virginia by Penn (2000) rendered a split ranking. Of those surveyed, 32% said the press was not an influence on decision-making, and another 39% reported media influence was low. These percentages are reflected in the present study. Nevertheless, Rose (2004) argues, "Like it or not, the media is part of the legislative process. The bottom line is that reporters and legislators need each other" flf. 4).


Each legislative session evolves into a complex, diverse, and dynamically changing process. Few, if any, generalizations transcend across all actors and time. The importance of each of these factors of influence can shift during the session. Therefore, what was deemed important at the beginning of the session may be upstaged by changing events and changing priorities mid-session, and regain major importance at the end. If practitioners are familiar with why politicians vote for or against proposed bills, then they may have greater influence on the policies enacted, and the content therein.

Some factors of influence may be masking other indicators not readily apparent. For example, the Governor may appear to be large factor of influence. However, the most important influence variable might actually be re-election, if the governor has some power or ability to shape the future for a particular legislator. In other words, these factors are multilayered with some influencing or controlling others. Unless one is familiar with the process and the present session, these nuances may go undetected, and limit practitioners from enhancing policy outcomes.

The legislative process is fluid. Developing ways of staying informed with the changing events is essential in effectively influencing policies one wants to shepherd through the process. Physical presence every day may not be possible, but monitoring news, events, and initiating regular contacts with those involved in the process may lead to more effective development and implantation of legislative policies.


First, the factors of influence in this study are numerically ranked, and the inter-relationship among and between these variables is complex. Further analysis of the inter-relationship between these variables may result in better understanding the summative relationship value of individual influence factors. Second, a national and international study should be undertaken to determine whether the ranking of these factors of influence are typical or unique. The findings in this study are limited to one state legislature. Other factors of influence may be significant, but absent in this study. For example, in this investigation legislators serve on a part-time basis. Therefore, some members spend time on other matters during the legislative session, causing them to miss meetings. The passage or failure of legislation is affected by legislators who fail to attend meetings. Research on additional factors of influence not addressed in this study will shed further light on legislative outcomes. Finally, each influence factor carries a degree of power. A study of the relative power of each factor of influence would render further insight into legislators' decision-making.


This descriptive study contributes to the body of knowledge about the factors of influence that guide the transformation of public will into public policy. State-level education policy-making will continue, and all those concerned with public schools can expand their impact upon the development of coherent education policies by having a better understanding of how and why decisions to pass or fail bills are made. This knowledge can help close the gap between state legislative policy-makers and education policy implementers, resulting in more effective outcomes for public schools and more positive benefits for the nation's school-aged youngsters.


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Author affiliation:

Kathy Canfield-Davis, University of Idaho

Sachin Jain, University of Idaho

Don Wattam, University of Idaho

Jerry McMurtry, University of Idaho

Mike Johnson, University of Idaho

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