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Record W4379617290 · doi:10.1353/iur.2016.a838380

Union labelling information for everyone who wants it

2016· article· en· W4379617290 on OpenAlexaboutno aff
John Lynn

Bibliographic record

VenueInternational Union Rights · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)ClothingBusinessAppealGrievancePackaging and labelingAdvertisingPolitical scienceMarketingLaw

Abstract

fetched live from OpenAlex

Union product labelling has taken a couple of dramatic steps into the digital age in Canada. There is a long tradition across North America of helping progressive shoppers identify union-made goods and services when they shop. As early as the 1880s many unions commonly marked their goods – labels in clothing, signs in shop windows, union ‘bugs’ on printed goods, stamps and other marks on product labels. Famously in the 1920s and 1930s the International Ladies Garment Workers Union, which dominated the needle trades across North America in that time, developed the ‘Look for the Union Label’ campaign including a song to drive home the message. The appeal for buying union in those early days was to provide some assurance to consumers that the goods they were buying were not produced in sweat shops. The workers who made your dress or shoes or canned goods were paid fairly, with reasonable benefits and a grievance procedure and other protections against high-handed employers or supervisors. This motivation still exists today, though most clothing is now made in Asian sweatshops offshore. Nonetheless, Canadian and US unions have traditionally printed lists of union-made goods in their city or region for distribution mainly to union members. In many regions special Union Label Trades Councils were formed for this purpose. The AFL-CIO and the Canadian Labour Congress both supported these initiatives, and the US organisation still publishes a union-made list though it is not comprehensive. In Canada there was no serious attempt to create a national list mainly because of the significant logistical challenges involved. Compounding the problem is the virtual disappearance of union labels in clothing, cards in shop windows and union bugs on consumer products today. The entreaty to ‘Look for the Union Label’ is futile. All which explains why, on January 1, 2012 we launched ShopUnion.ca. The website solves the distribution problem because our database is available to anyone anywhere with a computer, tablet or cell phone. It also solves the ‘union label’ problem because it uses product and manufacturer names rather than a tag, logo, sign or label to identify union-made goods. And we have made a point of collecting other regional or local lists whenever we can and dumping that information into our data base. Additionally, the data in the web site can be updated and changed on the fly, a major advantage over print. The web site uses the same search metaphor as Google. Items are identified with a list of key words, and users are encouraged to use the simplest, most common name for what they want. The site gives you the name and location of the business, its web site and the union. We post listings of products made anywhere in North America which are generally available for sale in stores across Canada and the United States. We do not pretend we have every union product made, but we are set up to accommodate as many as there are, and we are relentless in our search. We rely heavily on unions to share with us the names of companies they have under collective agreement. We have also sought out information on condiments, canned goods, breakfast cereals, snacks, candy, beer, wine, drugs and other such products which are quite often manufactured by large unionised companies. We then write a set of key words which represent the items or services they produce, and mount it in our data base. Listing services requires us to offer a region-specific search. It is not useful, for instance, to get a list of taxi cab companies in Toronto if you need a cab in Vancouver. Aside from listings, the two major challenges in managing ShopUnion.ca is attracting visitors to the site and playing the bills. We have found that social media and the communications apparatus of unions are our most productive means of informing progressive shoppers of the existence of the site. It is a free service to them, so that reduces the barriers to contact considerably. And our surveys have demonstrated to us that there is indeed a pentup demand for information on unionised goods. When people know where to go, they sign on. We...

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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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.628
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.6280.582

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 head0.014
GPT teacher head0.221
Teacher spread0.206 · 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.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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