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Record W4400585229 · doi:10.1108/jmh-09-2023-0096

Understanding and studying value as a duality

2024· article· en· W4400585229 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Management History · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Institutions
Canadian institutionsCarleton University
Fundersnot available
KeywordsDuality (order theory)Value (mathematics)SociologyPositive economicsEconomicsMathematicsStatisticsPure mathematics

Abstract

fetched live from OpenAlex

Purpose To cope successfully with the pressures imposed by a devastating pandemic and other challenges, companies and policymakers need to look at how they conceptualize, define, measure and operationalize “value”. This paper aims to support this conversation. Design/methodology/approach This study presents a historical review of how the value construct has been conceptualized over time, demonstrating that its history is one of tension and debate with conceptualizations swinging between objective (i.e. the value of something exists independent of the observers) and subjective (i.e. the value of something depends on the personal response of the observer to what is being considered) views over time. Findings This paper outlines the implications to researchers of value’s low construct clarity, offering suggestions designed to exploit rather than ignore the duality of the value construct. Instead of thinking of the value construct as being subjective or objective, this study recommends that scholars consider value’s objectivity and subjectivity as being interrelated and complementary. The paper recommends that researchers use both quantitative and qualitative methodologies in studying this construct. Research limitations/implications A major limitation of this paper is the word count limitation restricting the extent to which this paper could explore a more comprehensive list of the conceptualizations of value throughout history. Practical implications This paper presents practitioners with a nuanced understanding of value that should assist those interested in examining the worth of investments with observable expenses but less quantifiable outputs. Originality/value The authors have not found a similar analysis of the various conceptualizations of value.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.371

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.172
GPT teacher head0.247
Teacher spread0.075 · 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