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Record W4310340826 · doi:10.5281/zenodo.7376924

HUMAN RESOURCE MANAGEMENT IN THE CASE OF THE COMPANY LOBLAW

2022· article· en· W4310340826 on OpenAlex
VAFOKULOVA MEKHRUZA, OBLOKULOV BEGZOD, ROFEYEVA RUKHSHONA, MAKHMUDOVA ZARINA

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Practices
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessHuman resource managementKnowledge managementComputer science

Abstract

fetched live from OpenAlex

<strong>Abstract </strong> The purpose of the paper will center on functions that promote and protect equality within the organization, which has been once again voted as one of the top 100 companies in Canada, Loblaw’s. This paper will utilize a publicly available version of their code-of-conduct documents that outlines that firm’s commitment to equality within the workplace, and be contrasted with specific opinions of current employees of the aforementioned firm. The purpose will be to determine whether or not the firm’s HR policies and commitment to equality are realized within any given work environment within their organization. We will take a look at the standards for employment and equal opportunities laws of Canada (Similar to chapter 3 in the book), with specific focus on the working environment and making sure it is inclusive and allows for equal opportunity for all peoples. This mostly focuses on equality of genders and women of which has the greatest emphasis within this paper, but will also briefly touch on visible minorities and those of the LGBTQ+ community. Finally, this paper will also look at ways the firm can improve itself, as there are many issues that are not made generally public despite it being voted as one of the top companies in Canada to work for.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0020.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.039
GPT teacher head0.246
Teacher spread0.207 · 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