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Changing Models of Work in the Digital Platform Economy

2019· article· en· W2965248317 on OpenAlexaffabout
Greetje Frankje Corporaal, Hudson Sessions, Sirkka L. Järvenpää, Natalia Levina, Susan J. Ashford, Brianna Barker Caza, Jovana Karanović, Mareike Moehlmann, Hans Berends, Yuval Engel, Robert Wayne Gregory, Ola Henfridsson, Vili Lehdonvirta, Jennifer D. Nahrgang, Erin Marie Reid, Lior Zalmanson

Bibliographic record

VenueAcademy of Management Proceedings · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsMcMaster UniversityUniversity of Manitoba
Fundersnot available
KeywordsScholarshipIntermediaryGig economyWork (physics)Value (mathematics)Digital economySharing economyBossFunction (biology)Variety (cybernetics)ManagementPublic relationsComputer scienceMarketingBusinessWorld Wide WebPolitical scienceEngineeringEconomicsArtificial intelligence

Abstract

fetched live from OpenAlex

The proliferation of online labor platforms has significant consequences for the world of work, as workers adopt novel work roles in the gig economy, digital platforms function as new labor market intermediaries, and organizations reconfigure how they operate. This symposium aims to advance our understanding of this relatively novel phenomenon of platform-mediated work and explore implications for management scholarship. We address the ramifications of the digital platform economy for workers and organizations from organizational behavior, organizational theory, and information systems perspectives, thereby drawing on a variety of contexts. For workers, our symposium provides insights about how individuals can thrive in the so-called ‘gig economy’, the influence of platform algorithms on worker behavior, and the effects of managing multiple work roles. For firms, we explore perceptions of online platforms, motivations for adopting them, implications of online platforms for operations, and how capitalist and cooperative platform firms govern and create value. Finally, discussants will integrate our studies, draw conclusions, and offer suggestions for advancing the topic. No Boss, No Company, No Matter: How Workers Are Making It in the New World of Work Presenter: Brianna Barker Caza; U. of Manitoba Presenter: Susan J. Ashford; U. of Michigan Presenter: Erin Marie Reid; McMaster U. When Algorithms Are Your Boss: Algorithmic Management of Platform Work Presenter: Mareike Moehlmann; Warwick Business School Presenter: Lior Zalmanson; New York U. Presenter: Ola Henfridsson; Warwick Business School Presenter: Robert Wayne Gregory; U. of Navarra I’m Kind of a Big Deal . . . In My Other Job: The Effects of Status Inconsistency Across Work Roles Presenter: Hudson Sessions; U. of Oregon Presenter: Jennifer Nahrgang; Arizona State U. Bringing Work Back In: Theorizing Platform Sourcing as an Organizational Model for Knowledge Work Presenter: Greetje Frankje Corporaal; U. of Oxford Presenter: Vili Lehdonvirta; U. of Oxford Different Paths to Ecosystem Strategy: Platform Capitalism vs. Platform Cooperativism Presenter: Jovana Karanovic; KIN Research, VU Amsterdam Presenter: Hans Berends; Vrije U. Amsterdam Presenter: Yuval Engel; U. of Amsterdam

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 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 score0.651
Threshold uncertainty score0.223

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 communication0.0000.003
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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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