Evidence map›Paper›PMID 39995901›Full record

ArticleHeliyon2025

Do indigenous people get left behind? An innovative methodology for measuring the unmeasurable economic conditions and poverty from the poorest region of Luzon, Philippines.

Emmanuel A Onsay, Jomar F Rabajante

Abstract read
In one paragraph

Article in Heliyon, 2025. 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
–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

0 citing papers in PubMed.

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

2 authors.

Emmanuel A OnsayGraduate School, University of the Philippines Los Baños, Laguna, 4030, Philippines.
Jomar F RabajanteGraduate School, University of the Philippines Los Baños, Laguna, 4030, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the most vulnerable, neglected, and marginalized groups in society is indigenous communities. Their socioeconomic circumstances are intricate and varied. The oldest societal issue ever is poverty, which is also the hardest to solve. It is multifaceted and immeasurable, especially for the Agta Tabangnon, our Indigenous people. Research on indigenous peoples is qualitative in nature, whereas research on poverty is typically general, subject to significant sampling errors, and meant to inform national policy. Therefore, it is essential for economic development to measure multidimensional poverty and simulate the socioeconomic conditions for each tribe through full enumeration and disaggregation. This work puts forth fresh approaches to quantify the incalculable multifaceted poverty and socioeconomic conditions: (i) a thorough statistical analysis using diagnostic and descriptive analytics to examine socioeconomic situations; (ii) combining sophisticated econometrics and predictive analytics to measure multidimensional poverty; and (iii) integrating machine learning to model socioeconomic situations and prescriptive analytics to develop policy. Analysis reveals that poverty among tribes is closely tied to income, livelihood, and education, impacting various aspects of daily life, including housing, water, sanitation, health, and nutrition. The study develops multidimensional poverty indicators crucial for promoting economic development and poverty reduction among Indigenous communities. The study underscores the urgency of targeted policies and programs to address multidimensional deprivations faced by Indigenous communities, emphasizing the importance of data-driven approaches in improving welfare and promoting equitable socio-economic progress. Other researchers worldwide could replicate, reproduce, or reuse the suggested methods to assist indigenous peoples in reducing poverty and enhancing their well-being. It can be freely applied to focus policy on tribal economy, which has multiple dimensions and necessitates various forms of development initiatives.

Indexed as

Advanced econometricsData analyticsIndigenous communitiesMultidimensional povertyPhilippinesPolicySocioeconomic modelling

Identifiers

PMID39995901
PMCPMC11849085

What OpenQuestion holds

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Registered trials

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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.