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ERIC Number: EJ1350200
Record Type: Journal
Publication Date: 2022-Nov
Pages: 23
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0895-9048
EISSN: EISSN-1552-3896
Available Date: N/A
Partisan Predictors for Collective Bargaining Agreement Items
Educational Policy, v36 n7 p1679-1701 Nov 2022
The United States is rare among nations in its highly decentralized process for negotiating collective bargaining agreements with local teachers' unions. To determine whether partisanship can predict these highly localized decisions, I construct an original database of Pennsylvania collective bargaining agreements (CBAs) merged with publicly available voter registration records to predict the presence of high-profile contract items. Using spatial autoregression and probit regression, I reveal that the partisanship of a school district is a significant predictor for fewer seniority protections but not for lower salaries. These partisan relationships can guide both district administrators and union leaders in future negotiations.
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub-com.bibliotheek.ehb.be
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Pennsylvania
Grant or Contract Numbers: N/A
Author Affiliations: N/A