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Generalists’ career in modern organizations and education: Theoretical review

2023· article· en· W4386451807 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

VenueОрганизационная психология · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Resources and Workforce
Canadian institutionsCarleton University
Fundersnot available
KeywordsGeneralist and specialist speciesAdaptation (eye)Resource (disambiguation)Public relationsCareer developmentProfessional associationKnowledge managementEngineering ethicsPolitical scienceBusinessSociologyPsychologyPedagogyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Purpose. In this article, we continue to analyze the actual problem of modern organizations, which is associated with changing forms of professionalism and the place of a professional in the organization. In conditions of uncertainty and socio-economic changes, the so-called universal professionals are of increasing interest, who demonstrate a focus on a wide range of tasks they solve and activities they perform. Findings. It is shown that specialists of a wide profile are increasingly indemand today in organizations and society. They are the most important resource for the organization’s adaptation to changing external and internal conditions. We look at the reasons why organizations need generalist professionals. The problems caused by the peculiarities of their involvement in solving various goals of the organization and different career prospects are highlighted. Various career tracksand career development directions of such employees in organizations are shown. Based on the analysis, the conditions under which generalists build a successful career and chances for employment are highlighted.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.329
Teacher spread0.305 · 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