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Record W2588559877

You Can't Fire Me: The Problems with Wrongful Dismissal Damages in Canada

2017· article· en· W2588559877 on OpenAlexaffabout
Chenyang Li

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsWestern University
Fundersnot available
KeywordsDismissalDamagesUnfair dismissalLawLabour lawContext (archaeology)WarrantCommon lawPlaintiffPolitical scienceBusinessLaw and economicsEconomics
DOInot available

Abstract

fetched live from OpenAlex

The assessment of wrongful dismissal damages in Canadian law has long been governed by the principles established in Bardal v Globe & Mail Ltd. Although this model of analysis has been met with near universal approval in every decision-making forum in Canada, the principles underlying Bardal warrant further discussion. This work focuses on the contractual core of employment disputes and analyzes the interpretive framework for common law claims for wrongful dismissal. It will show that the traditional law of private remedies has been distorted in the context of wrongful dismissal as a result of the wholesale adoption of the Bardal Factors. The Bardal approach requires courts to depart from traditional doctrines of remedies and contract law and extends beyond the traditional goal of restitutio in integrum to a distributive theory of damages. This ultimately results in outcomes that depart from the original goal of wrongful dismissal remedies: protecting society’s vulnerable workers from unfair employment practices. This paper will suggest that damages from the breach of the employment contract should be objectively assessed from the intention of the parties at the time of contract formation. The courts in Lazarowicz and Bartlam have provided useful guidance with respect to how this method can be successfully applied. Returning to the goal of restitutio in integrum and corrective justice in wrongful dismissal damages would provide needed predictability and stability in employment relationships.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.000
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 head0.084
GPT teacher head0.317
Teacher spread0.233 · 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.

Study designObservational
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
Published2017
Admission routes2
Has abstractyes

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