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Record W7034698888

What’s wrong with dismissal law? How can the law be reformed to safeguard against the effects of dismissal?

2024· dissertation· en· W7034698888 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typedissertation
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsDismissalLegislatureLabour lawUnfair dismissalCommon lawWork (physics)Strengths and weaknesses
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores dismissal law in England and Wales at a sociolegal level. It uses existing international theory and data and responses from 38 study participants to identify the health, social, and family effects of dismissal. The theory reveals that work transcends several aspects that are central to daily living. It reveals critical social and economic dimensions, which are both related to health. The data identifies considerable adverse consequences arising from dismissal, which impact societal stability, highlighting the need for dismissal to be understood as a social phenomenon. It contextualises these findings against the dismissal law system to identify any weaknesses and suggest reforms to offer employees better protection from dismissal and its aftermath. Analysis of the common law and the contract of employment reveals ingrained biases that have benefitted employers at the expense of workers and have damaged job security. In reviewing how dismissal law does not fully protect employees, economic and capitalist mentalities towards employment are revealed, which have had the effect of harming the discourse on progressive advancement in dismissal law. The thesis highlights the lack of clear-cut evidence on the claim that dismissal law is bad for the economy, instead offering alternative economic explanations, suggesting that the legislature must look beyond economics to the identifiable consequences of dismissal. In doing so, the thesis argues that full recognition and protection of employees’ interests require structural changes. These changes must come from the legislature and judiciary. It argues that the state should play an active role in mitigating the effects of dismissal through progressive welfare policies, with the potential for Universal Basic Income to address the wide-ranging consequences of financial detriment following dismissal. In addition, it argues that the government must take a less restrictive approach to trade unions, which offer employees vital job security and reduce dismissal probability. After this, the thesis critically analyses access to justice, with evidence showing that the reduction in legal aid, the costs involved in bringing a claim, and the complex nature of the employment tribunal system have impacted the ability of claimants to get justice. It argues that the rule that employees must have worked for two years to be able to claim unfair dismissal lacks empirical support, is a significant barrier to justice, is discriminatory, and must be removed or shortened. It goes on to consider the common law approach to distress damages, arguing that the reluctance to permit such damages fails to fully recognise the social importance of dismissal and is based on an assumption that the employment relationship is akin to a commercial exchange rather than being relational. It proposes that this must change, with Canadian and New Zealand approaches offering a solution. After this, it shows that, in practice, the tests of fairness and reasonableness under section 98 of the Employment Rights Act 1996 afford too much latitude to an employer to dismiss a worker, are doctrinally flawed, and represent a bias in legislative and judicial thinking towards dismissal. Building on this, the thesis suggests several solutions to overcome this, considering comparative and theoretical approaches.

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)0.034
metaresearch head score (Gemma)0.090
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 score0.070
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.090
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0110.040
Scholarly communication0.0180.021
Open science0.0030.006
Research integrity0.0130.017
Insufficient payload (model declined to judge)0.0040.002

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 head0.013
GPT teacher head0.229
Teacher spread0.215 · 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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