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Record W4406092236 · doi:10.46692/9781529236972.007

Expanding the Boundaries of Industrial Relations as a Field of Study: The Role of ‘New Actors’

2024· other· en· W4406092236 on OpenAlexaboutno aff
Steve Williams

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)Industrial relationsEconomic geographyPolitical scienceSociologyGeographyMathematicsLaw

Abstract

fetched live from OpenAlex

Work on so-called ‘new actors’ in industrial relations (Heery and Frege, 2006; Cooke and Wood, 2014) has not only added to our knowledge and understanding of industrial relations but also highlighted its distinctiveness and vitality as a field of study, and expanded its boundaries. But what do we mean by an industrial relations ‘actor’? Influenced by Dunlop's (1958) concept of an ‘industrial relations system’, the field was traditionally dominated by a concern with understanding collective relations between workers, represented by trade unions, and employers, often organized in employers’ associations (Heery and Frege, 2006). The label ‘new’ can thus be applied to actors – individuals, organizations, institutions and movements – that either did not used to have much of a role in industrial relations or did have one but were neglected. Much of the credit for stimulating a greater concern with new actors must go to Bellemare (2000). His study of the Canadian city of Montreal showed the important influence over industrial relations exercised by public transport users. The work of bus drivers, for example, was affected in some important ways by the attitudes and expectations of passengers. Bellemare's (2000) principal theoretical contribution was to conceptualize the nature of an industrial relations actor based on the extent of their involvement at three levels – the workplace, the organization and wider society, respectively – and their impact. Further studies of ‘end users’ in health and social care highlight their importance as actors in industrial relations. For example, the activities of patients’ representatives can influence how individual staff are managed in hospital settings (Bellemare et al, 2018). Moreover, empowering users of care services has important implications for how carers’ work is organized (Kessler and Bach, 2011). However, Bellemare's (2000) approach, with its emphasis on being influential at all three levels and the continuity of such influence, is perhaps too restrictive, potentially excluding actors who play an important part in industrial relations but whose involvement is restricted to a single level or is intermittent (Abbott, 2006; Kessler and Bach, 2011). In the case of certain actors, it is not that they are necessarily ‘new’ but rather that their role has become more prominent or better understood. Some examples are as follows. John Logan (2006) detailed the important contribution made by anti-union law firms and consultants to corporate efforts to suppress unionization in the US.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.065
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.065
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0170.137
Scholarly communication0.0310.048
Open science0.0030.027
Research integrity0.0100.014
Insufficient payload (model declined to judge)0.0050.001

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 head0.042
GPT teacher head0.351
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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