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Record W4415493363 · doi:10.1002/uar2.70023

Effectiveness of Facebook groups in enhancing the capacity of rooftop gardeners

2025· article· en· W4415493363 on OpenAlexaff
Khondokar H. Kabir, Jannatul Ferdows, Saifur Rahman, Ataharul Chowdhury, Md. Asaduzzaman Sarker, S.M. Asik Ullah, Mohammed Nasir Uddin

Bibliographic record

VenueUrban Agriculture & Regional Food Systems · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSocial mediaIncentiveBridging (networking)Information sharingAgricultureTourismResource (disambiguation)

Abstract

fetched live from OpenAlex

Abstract Rooftop farming is a modern way of growing food in cities that uses unused rooftop spaces to promote local food production. A lack of knowledge and limited access to technical assistance are major obstacles that hinder the practice. Furthermore, traditional agricultural extension services currently provide insufficient incentives to encourage this practice. These limitations, however, can be addressed by providing real‐time information and support through social media platforms such as Facebook. This study investigates the extent to which Facebook supports the information needs of rooftop gardeners within the framework of virtual communities of practice. It also seeks to assess the perceived usefulness of information shared in Facebook groups for enhancing the capacity of rooftop gardeners. Data were collected from 120 rooftop gardeners in Bangladesh through an online survey administered via Google Forms and distributed across two popular Facebook groups. Findings indicate that information sharing in Facebook groups assists rooftop gardeners in planning, acquiring, and utilizing resources, carrying out intercultural operations, and determining optimal harvesting and storage practices. Overall, Facebook can play a significant role in bridging the information gap among rooftop gardeners and in enhancing their skills. Moreover, it represents a valuable resource for urban dwellers interested in engaging in rooftop gardening.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.200
Teacher spread0.186 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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