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Record W2953047983 · doi:10.5539/ass.v13n4p175

Solving Society’s Big Ills, A Small Step

2017· article· en· W2953047983 on OpenAlexvenueno aff
Ravi Kashyap

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsnot available
Fundersnot available
KeywordsIgnoranceLanguage changeExtension (predicate logic)Unintended consequencesOverconfidence effectWelfarePublic relationsPsychologySocial psychologyBusinessSociologyPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

We look at a collection of conjectures with the unifying message that smaller social systems, tend to be less complex and can be aligned better, towards fulfilling their intended objectives. We touch upon a framework, referred to as the four pronged approach that can aid the analysis of social systems. The four prongs are:1. The Uncertainty Principle of the Social Sciences2. The Objectives of a Social System or the Responsibilities of the Players3. The Need for Smaller Organizations4. Redirecting Unintended OutcomesSmaller organizations mitigating the disruptive effects of corruption is discussed and also the need for organizations, whose objective is to foster the development of other smaller organizations. We consider a way of life, which is about respect for knowledge and a desire to seek it. Knowledge can help eradicate ignorance, but the accumulation of knowledge can lead to overconfidence. Hence it becomes important to instill an attitude that does not knowledge too seriously, along with the thirst for knowledge. All of this is important to create an environment that is conducive for smaller organizations and can be viewed as a natural extension of studies that fall under the wider category of understanding factors and policies aimed at increasing the welfare or well-being to society.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.052
GPT teacher head0.247
Teacher spread0.195 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2017
Admission routes1
Has abstractyes

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