Evidence map›Paper›PMID 33067395›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Voluntary leadership and the emergence of institutions for self-governance.

Krister P Andersson, Kimberlee Chang, Adriana Molina-Garzón

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Krister P AnderssonInstitute of Behavioral Science, University of Colorado-Boulder, Boulder, CO 80309; krister@colorado.edu.ORCID 0000-0002-9320-8155
Kimberlee ChangDepartment of Political Science, University of Colorado-Boulder, Boulder, CO 80309.ORCID 0000-0002-3976-7108
Adriana Molina-GarzónDepartment of Political Science, University of Colorado-Boulder, Boulder, CO 80309.ORCID 0000-0001-9685-4550

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Strong local institutions are important for the successful governance of common-pool resources (CPRs), but why do such institutions emerge in the first place and why do they sometimes not emerge at all? We argue that voluntary local leaders play an important role in the initiation of self-governance institutions because such leaders can directly affect local users' perceived costs and benefits associated with self-rule. Drawing on recent work on leadership in organizational behavior, we propose that voluntary leaders can facilitate a cooperative process of local rule creation by exhibiting unselfish behavior and leading by example. We posit that such forms of leadership are particularly important when resource users are weakly motivated to act collectively, such as when confronted with "creeping" environmental problems. We test these ideas by using observations from a laboratory-in-the-field experiment with 128 users of forest commons in Bolivia and Uganda. We find that participants' agreement to create new rules was significantly stronger in group rounds where voluntary, unselfish leaders were present. We show that unselfish leadership actions make the biggest difference for rule creation under high levels of uncertainty, such as when the resource is in subtle decline and intragroup communication sparse.

Indexed as

Cooperative BehaviorGovernmentLeadershipBoliviaHumansStakeholder ParticipationUgandaVolunteerscommon-pool resourcesgovernanceleadershipsustainability

Identifiers

PMID33067395
PMCPMC7959538

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.