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Record W7000834921

Greening Hotels and Fair Labour Practices

2022· report· en· W7000834921 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAccommodationGreeningLeverage (statistics)SustainabilityPreferenceEnvironmentally friendlyScale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

In recent years, a number of labour union strategic initiatives have been developed which seek to leverage consumer preference against employers in the accommodation services sector. These programs largely focus on rating and certifying hotels based upon environmentally and socially responsible behaviour and labour friendly practices. In part, the campaigns are a response to the perceived 'green-washing' of hotels through voluntary, self-reporting rating systems. This paper examines three union campaigns that recommend hotels according to social and environmental criteria: The Fair Hotels campaign (Ireland); the First Star program (Australia); and INMEX (United States and Canada). We find that limitations are related to the geographic scale of the campaigns and their inability to advocate for any significant shift toward a more socially and environmentally sustainable accommodation services sector.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.177
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0020.001
Scholarly communication0.0010.014
Open science0.0030.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.210
Teacher spread0.173 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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