MétaCan
Menu
Back to cohort
Record W3094329069 · doi:10.1177/0899764020966046

Businesses Venturing Into the Social Domain During the Covid-19 Pandemic: A Motivation and Ability Perspective

2020· article· en· W3094329069 on OpenAlexaff
Yongjian Bao, Zhe Shen, Wenlong Yuan

Bibliographic record

VenueNonprofit and Voluntary Sector Quarterly · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of ManitobaUniversity of Lethbridge
Fundersnot available
KeywordsTypologyPerspective (graphical)BusinessCoronavirus disease 2019 (COVID-19)Value (mathematics)PandemicValue creationMonopolistic competitionMarketingPublic relationsIndustrial organizationEconomicsMarket economySociologyPolitical science

Abstract

fetched live from OpenAlex

Many businesses have joined governments and nonprofit organizations to serve the social needs under the tremendous pressure of Covid-19. We propose that businesses that expanded into the social domain during the Covid-19 crisis differ significantly from each other and vary extensively in value creation. We extend the motivation and ability framework to derive a typology of businesses under this situation and conceptualize value creation behaviors in both a free market and a monopolistic market with the governments as the buyer.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.045
GPT teacher head0.277
Teacher spread0.232 · 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 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNonprofit and Voluntary Sector QuarterlySame topicCorporate Social Responsibility ReportingFrench-language works237,207