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Record W1506564125

Institutionalization of Business Improvement Districts: A Longitudinal Study of the State Laws in the United States

2013· article· en· W1506564125 on OpenAlexaboutno aff
Göktuğ Morçöl, Douglas Gautsch

Bibliographic record

VenuePublic Administration Quarterly · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionalisationAccountabilityState (computer science)Public administrationDemocracyPolitical scienceGovernment (linguistics)Economic JusticeLocal governmentLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACTThe institutionalization of business districts (BIDs) is investigated with analyses of the state enabling laws in the United States. The results indicate that no distinct institutional BID form has emerged yet, but there is a process of institutionalization. This process can be observed in the names used for BIDs in the laws, their governing models and the methods of determining their board membership. The name improvement district has been used with an increasing frequency in the laws. Of the three BID governing models-subunits of local governments, autonomous public authorities, and nonprofit corporations-the last has been adopted more frequently in recent decades. The governing bodies of BIDs may be appointed or elected, but the elected board model was adopted more frequently in recent decades.Keywords: business districts; special districts; institutionalizationAcknowledgementWe gratefully acknowledge Dr. Carol Becker's contribution to this study by sharing with us the detailed results of the BID survey she and her colleagues had conducted in 2010.Business districts (BIDs) have been established in all states of the United States, most provinces of Canada, a few countries in Europe (United Kingdom, Ireland, Germany, and the Netherlands), and South Africa and a considerable size of BID literature has been built in recent decades. BID researchers investigated their implications for democratic participation and accountability (Barr, 1997; Briffault, 1999; Hochleutner, 2008; Justice & Skelcher, 2009), BID-local government relations (Morcol & Zimmermann, 2008; Wolf, 2008), and their successes and failures in helping solve urban problems (Hoyt, 2005; Ellen, Schwartz & Voicu, 2007; Cook & MacDonald, 2011).After two decades of research, there still is a need to formulate a common conceptualization of BIDs, however. An important problem is whether BIDs should be conceptualized as a distinct form of local government or a mixture of different institutional forms. There are two sets of conceptual issues within this problem. First, is there a single and coherent BID institutional form? Justice and Skelcher (2009) argue that it is possible to identify an ideal typical BID institutional form, despite the considerable functional and institutional diversity among the BIDs in the different states of the United States and other countries (p. 740). Second, are BIDs distinguishable from other forms of special districts? This is an important question, because BIDs are often defined in terms of their similarities with and differences from special districts (e.g., Kennedy, 1996; Briffault, 1999). To answer these questions, we analyzed the definitions and descriptions of BIDs in the enabling laws of the 50 states of the United States, Washington DC, and Puerto Rico.This comprehensive study of the state laws is needed because the conceptualizations of BIDs in the current literature are based on limited empirical investigations and legal analyses. Mitchell's (1999) nationwide survey in the United States in the later 1990s identified BIDs in 42 states and Washington, DC. Becker and her colleagues' survey in 2010 identified BIDs in 48 states-the only exceptions being North Dakota and Wyoming-and Washington DC (Becker, 2010; Becker, Grossman, & Dos Santos, 2011). However, the empirical and legal studies typically focus on few selected cases and/or few state laws. This narrow focus in the studies does not constitute a sufficient basis for a comprehensive conceptualization of BIDs.The empirical BID studies have focused primarily on six states and Washington, DC: California (Brooks, 2006, 2007; Cook & MacDonald, 2011; Lloyd, McCarthy, McGreal & Berry, 2003; MacDonald, Stokes & Bluthenthal, 2010; Meek & Hubler, 2008; Stokes, 2008), Pennsylvania (Hoyt, 2005; Stokes, 2006; Morcol & Patrick, 2008; Dilworth, 2010)1, New York (Ellen, Schwartz & Voicu, 2007; Gross, 2008; Meltzer, 2011), Maryland (Baer, 2008; Baer & Feiock, 2005; Baer & Marando, 2001), New Jersey (Justice & Goldsmith, 2008; Ruffin, 2010), Georgia (Ewoh & Zimmermann, 2010; Morcol & Zimmermann, 2008), and Washington, DC (Mallet, 1993; Schaller & Modan, 2005; Wolf, 2006). …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.355
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations11
Published2013
Admission routes1
Has abstractyes

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