Evidence map›Paper›PMID 35213552›Full record

ArticlePloS one2022

Do windy areas have more wind turbines: An empirical analysis of wind installed capacity in Native tribal nations.

Laura E Evans, Nives Dolšak, Aseem Prakash

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 52% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Laura E EvansEvans School of Public Policy and Governance, University of Washington, Seattle, Washington, United States of America.
Nives DolšakSchool of Marine and Environmental Affairs, University of Washington, Seattle, Washington, United States of America.ORCID 0000-0002-8325-3155
Aseem PrakashDepartment of Political Science, University of Washington, Seattle, Washington, United States of America.ORCID 0000-0002-7364-0135
University of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The decarbonization of the electricity sector is leading to a substantial increase in the demand for wind energy. Will tribal nations, which account for 7.8% of utility-scale wind capacity, benefit from this policy shift? To examine why tribal nations vary in translating wind energy potential into wind installed capacity, we have constructed an original dataset of the potential as well as the location of wind turbines across tribal nations. Our statistical analysis of 286 tribal nations suggests that wind energy potential is not associated with wind installed capacity. Instead, casino square footage, a proxy for tribal nation's administrative capacity and business acumen, is associated with wind installed capacity. Political orientation plays a role as well: tribal nations are more likely to have wind installed capacity when they value tribal sovereignty. While tribes suffering from natural disasters do not install more wind turbines, those receiving federal grants for wind energy projects, and located in states that already have a substantial number of wind turbines, are more apt to have wind turbines. Surprisingly, tribes located in states with renewable portfolio standards do not show an association with installed wind turbines capacity.

Indexed as

ElectricityIndigenous PeoplesRenewable EnergyHumansNatural DisastersPower PlantsResearch DesignWind

Identifiers

PMID35213552
PMCPMC8880873
OpenAlexW4214609876

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.