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Record W4385364884 · doi:10.3982/ecta20355

Ideology and Performance in Public Organizations

2023· article· en· W4385364884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEconometrica · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic Procurement and Policy
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsIdeologyProcurementBureaucracyPresidential systemPoliticsPresidential electionPublic administrationCivil servicePublic serviceService (business)Political economyPolitical scienceEconomicsPublic relationsLawManagementEconomy

Abstract

fetched live from OpenAlex

We combine personnel records of the United States federal bureaucracy from 1997 to 2019 with administrative voter registration data to study how ideological alignment between politicians and bureaucrats affects turnover and performance. We document significant partisan cycles and turnover among political appointees. By contrast, we find no political cycles in the civil service. At any point in time, a sizable share of bureaucrats is ideologically misaligned with their political leaders. We study the performance implications of this misalignment for the case of procurement officers. Exploiting presidential transitions as a source of “within‐bureaucrat” variation in political alignment, we find that procurement contracts overseen by misaligned officers exhibit greater cost overruns and delays. We provide evidence consistent with a general “morale effect,” whereby misaligned bureaucrats are less motivated to pursue the organizational mission. Our results thus help to shed some of the first light on the costs of ideological misalignment within public organizations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.007
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.030
GPT teacher head0.220
Teacher spread0.190 · 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