Evidence map›Paper›PMID 32304066›Full record

ArticleEnvironmental science and pollution research international2020

Climate change-induced human conflicts and economic costs in Pakistani Punjab.

Khuda Bakhsh, Karim Abbas, Sarfraz Hassan, Muhammad Asim Yasin, Rafaqet Ali, Najid Ahmad, Muhammad Waqas Alam Chattha

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Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

7 authors.

Khuda BakhshDepartment of Management Sciences, COMSATS University Islamabad, Vehari Campus, Vehari, Pakistan. kbakhsh@ciitvehari.edu.pk.
Karim AbbasInstitute of Agricultural and Resource Economics, University of Agriculture, Faisalabad, Pakistan.
Sarfraz HassanInstitute of Agricultural and Resource Economics, University of Agriculture, Faisalabad, Pakistan.
Muhammad Asim YasinDepartment of Management Sciences, COMSATS University Islamabad, Vehari Campus, Vehari, Pakistan.
Rafaqet AliDepartment of Management Sciences, COMSATS University Islamabad, Vehari Campus, Vehari, Pakistan.
Najid AhmadSchool of Business, Hunan University of Science and Technology, Hunan, China.
Muhammad Waqas Alam ChatthaUniversity of Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding causes of interpersonal conflicts, related costs, and the effects on investment in agriculture are important concerns of social sciences. The present study was designed to explore these aspects in relation to climate change, since rising temperature and precipitation are considered crucial causal factors in fueling interpersonal conflicts. The study used cross-sectional data collected from rural farm households from a large district of Pakistani Punjab. Cost of conflicts was estimated using standard economic methods whereas factors affecting interpersonal conflicts were estimated through employing logit model. The study found that interpersonal conflicts cost US$135 per month for following the proceedings of the conflicts filed in the court. Households involved in conflicts spent significantly very few resources in purchasing farm inputs which in turn declined productivity of maize (28%) and sugarcane (19%). Warm temperature, precipitation, and windstorm were perceived by households as causal factors for interpersonal conflicts. Socioeconomic characteristics namely, farm size, livestock, family size, and high monthly income of household, were significantly associated with interpersonal conflicts. The study concludes important policy implications.

Indexed as

Climate ChangeFamily CharacteristicsAgricultureAnimalsCross-Sectional StudiesHumansIncomePakistanSocioeconomic FactorsClimate changeCosts of conflictsFarm householdsInterpersonal conflictsInvestment in farm inputs

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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.