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Record W4393259359 · doi:10.47941/ijecop.1765

Impact of Information Provision on Decision-Making

2024· article· en· W4393259359 on OpenAlexaff
Jade Okello

Bibliographic record

VenueInternational Journal of Economic Policy · 2024
Typearticle
Languageen
FieldComputer Science
TopicInformation Architecture and Usability
Canadian institutionsSaint Paul University
Fundersnot available
KeywordsBusinessComputer science

Abstract

fetched live from OpenAlex

Purpose: The general purpose of the study was to explore the impact of information provision on decision making. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to information provision on decision making. The study offered significant insights into how information provision impacts decision-making across various domains. Through comprehensive review and synthesis of empirical evidence, it emphasized the crucial role of information quality and accessibility in shaping decision outcomes. Tailoring information provision strategies to diverse stakeholders' needs was highlighted, alongside the bidirectional relationship between information processing and decision outcomes. Ethical considerations, such as transparency and privacy, were stressed to ensure equitable decision outcomes. The findings underscored the transformative potential of effective information provision, offering actionable insights for stakeholders. Interdisciplinary collaborations and evidence-based interventions were advocated for driving positive societal change. Unique Contribution to Theory, Practice and Policy: The Information Processing theory, Theory of Planned Behaviour and Social Exchange theory may be used to anchor future studies on information provision on decision making. The study offers comprehensive recommendations across theoretical, practical, and policy domains. It calls for further theoretical exploration into cognitive processes underlying decision-making and interdisciplinary collaboration. Practically, it advocates for tailored information provision interventions that match diverse decision contexts and user preferences, alongside transparent and accessible information dissemination practices. Policy-wise, the study urges evidence-based communication strategies, regulatory frameworks promoting transparency and accountability, and educational initiatives fostering information literacy. These recommendations aim to empower individuals, organizations, and policymakers to navigate information landscapes effectively, promote informed decision-making, and address information inequalities. Keywords: Information Provision, Decision-Making, Stakeholders, Ethical Considerations

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.099
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.004
Scholarly communication0.0100.005
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.009
GPT teacher head0.346
Teacher spread0.337 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2024
Admission routes1
Has abstractyes

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