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Record W2918291660

Discrimination and Family Status: The Test, the Continuing Debate, and the Accommodation Conversation

2018· article· en· W2918291660 on OpenAlexaboutno aff
Sheila Osborne-Brown

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
Fundersnot available
KeywordsPrima facieAppealContext (archaeology)Test (biology)ConversationEmployment discriminationAccommodationLawInterlocutoryPolitical scienceConstructivePsychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

There has been much uncertainty about the interpretation of as a prohibited ground of discrimination in the context of parent-to-child caregiving. In Canada (Attorney General) v Johnstone, the Federal Court of Appeal appeared to have eliminated the confusion. However, the test has been criticized for inserting accommodation principles into the determination of a prima facie case. The Ontario Human Rights Tribunal has rejected the idea of a special test for whether an employee has proven family status discrimination. Yet a specific test to establish a prima facie case of family status is consistent with previous decisions relating to other prohibited grounds of discrimination. The Johnstone test assesses whether an employee has a caregiving need that would trigger a request for accommodation in the workplace, and is consistent with determining when an employee's personal family responsibility ends and an employer's responsibility begins. However, rather than arguing about legal tests in an adversarial forum, a more satisfactory solution to addressing family status needs is to address them in the workplace. The article highlights the need for constructive communication between employees and managers to respond to work/family conflicts and outlines guidance from human rights commissions as to when a family situation should start an accommodation conversation and how to have it.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.646
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.031
GPT teacher head0.317
Teacher spread0.286 · 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.

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
Published2018
Admission routes1
Has abstractyes

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