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Record W4392161538 · doi:10.46692/9781529222975.003

Unravelling the Meaning of ‘Social Origin’ Discrimination in Conventions of the International Labour Organization (ILO) and its Applications in the Digital Age

2023· other· en· W4392161538 on OpenAlexaboutno aff
Angelo Capuano

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicInternational Labor and Employment Law
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)SociologyPolitical scienceEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Introduction As noted in Chapter 1, discrimination on the basis of ‘social origin’ is prohibited by ILO conventions. Article 1 of ILO 111 prohibits discrimination on the basis of grounds including ‘social origin’ and article 5 of ILO 158 prohibits termination of employment on the basis of grounds including ‘social origin’. The term ‘social origin’ is not, however, defined in these instruments. In 1957 and 1958, when delegates from different countries were debating the meaning of the term ‘social origin’ in the proposed ILO 111 , there was much uncertainty from various delegates as to what the term meant or how it would apply in certain countries, such as Canada and Sweden. Approximately 55 years later, when Australian politicians and others turned their attention to the concept of ‘social origin’ discrimination at public hearings into the proposed Human Rights and Anti-Discrimination Bill 2012 (Cth), very little progress had been made in understanding the concept of ‘social origin’ (and ‘social origin’ discrimination). Some Australian senators believed that ‘social origin’ has an ‘almost limitless meaning’, is ‘vague’ and ‘almost meaningless’. This chapter sets out to achieve two main objectives. First, it clarifies the meaning of ‘social origin’ in ILO conventions to show that, far from being vague or meaningless, the term has a clear meaning in ‘jurisprudence’ developed by the ILO's supervisory bodies. Second, it explains why ILO jurisprudence matters in domestic contexts, particularly Australia and South Africa. Part I will explain the ILO supervisory system and the respective roles of two supervisory bodies, the ILO Committee of Experts on the Application of Conventions and Recommendations (‘Committee of Experts’) and Commissions of Inquiry, in interpreting ILO conventions. Part II will explain the concept and scope of ‘discrimination’ in ILO jurisprudence, to set the stage for an analysis of discrimination based on ‘social origin’. Part III will then analyse the reports of ILO supervisory bodies and the travaux préparatoires (preparatory works) of relevant treaty to elucidate the meaning of ‘social origin’ in ILO conventions, and clarify how this type of discrimination might occur. Finally, Part IV will rely on legal rules of interpretation to explain why this ILO jurisprudence matters in domestic contexts, particularly in Australia and South Africa. I. The ILO and ILO supervisory bodies One function of the ILO is to supervise the implementation of ILO conventions and recommendations in member states.

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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)0.004
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.030
Scholarly communication0.0120.015
Open science0.0010.006
Research integrity0.0050.007
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 head0.029
GPT teacher head0.310
Teacher spread0.281 · 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
GenreOther

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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