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Record W4401385684 · doi:10.33423/jabe.v26i3.7139

A Corporate Managerial Framework for Collaboration Skills Training of Employees From Formerly Oppressed Communities

2024· article· en· W4401385684 on OpenAlexvenueno aff
Kenyatta Rosier, Felipe Llaugel, D.S. Ridley

Bibliographic record

VenueJournal of Applied Business and Economics · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
Fundersnot available
KeywordsGross domestic productHarmRule of lawEconomic growthEconomicsSociologyPsychologyPolitical scienceSocial psychologyLawPolitics

Abstract

fetched live from OpenAlex

It is widely recognized that countries scoring high in capitalism, democracy, and the rule of law (CDR) tend to have impressive levels of real per capita gross domestic product (GDP) adjusted for purchasing power parity (GDPppp). However, the key to the rule of law is collaboration, and the ability to work together may have been eroded in communities that have experienced past traumas such as forced labor, excessive discrimination and exposure to harmful chemicals. These distressing outcomes can be inherited by future generations through negative epigenetic transgenerational psycho-sequela, leading to poor academic and employment performance, low income, self-harm, negative community relations, and increased aggression. This paper aims to explore the development of a managerial framework for rehabilitating psychological health that aims to revive lost collaboration skills. The originality of this work lies in the managerial framework that facilitates the restoration of collaboration skills, which are fundamental to exceptional economic growth and higher average income countrywide.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.031
GPT teacher head0.231
Teacher spread0.201 · 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 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
Published2024
Admission routes1
Has abstractyes

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