MétaCan
Menu
Retour à la cohorte
Enregistrement W2772349984

The Wealth of Humans: Work, Power and Status in the Twenty-First Century

2017· article· en· W2772349984 sur OpenAlexvenueaboutno aff
Donald R. Officer

Notice bibliographique

Revue˜The œinnovation journal · 2017
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Development and Digital Transformation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésUnemploymentPower (physics)SociologyEconomicsEconomic growth
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Ryan Avent Wealth of Humans: Work, Power and Status in the Twenty-first Century New York, NY: St. Martin's Press, 2016In this well-argued book, Economist writer Ryan Avent lays out a bleak vista stretching forward as far as the jaundiced eye can see. What's mostly missing in this melancholy scenario is jobs. Looking back over the decades, the most insightful economists of the twentieth century just did not see this coming. What they did foresee was a steady attrition of all work susceptible to automation, globalization and other concomitant efficiencies coming on stream. Commenting during the bleaker thirties, John Maynard Keynes exhibited more than a little concern over what could happen to a future society inundated with a great surplus of leisure time to spend! Some of you may remember those fanciful, gee-whiz worries of decades past.But even if you count unemployment as a form of leisure, the surplus we really need worry about is inequality. Most essential commodities and many services are in oversupply worldwide. However, we remain far away from solving the social problem of distribution. In the oft-quoted words of science fiction writer William Gibson (2003), The future is already here; it's just not very evenly distributed. Because of the way contemporary society continues to organize itself, inequality, joblessness, gluts and the absence of meaningful growth continue to coexist.In the UK imprint of this book, the second half of the title reads Work and its Absence in the Twenty-first Century, which summarizes the author's theme. There is much more to say though than that, including surprises which may make you angry if you are not among the favoured few in the highest income percentiles. Among those surprises may be the discovery that automation and robotics are not alone in the systematic, structural replacement of skilled work. You might have to give way to other workers very close to home, but less protected or qualified. Paradoxically, a better educated workforce, once a rising tide to raise generations of good careers, has created an accreditation glut. Employers can demand higher levels of qualification for entry level positions, yet pay successful applicants much less than before. We've all seen this.The picture gets even bleaker. While job seekers contort their lives into mangled pretzels to look good on their resumes, others, whose only significant contribution to the world might be the inheritance of a strategically located tract of land or the chance purchase of an under rated block of shares, are arbitrarily set for life. Huffington Post (Tencer, 2016) reports that if you owned an average house in Canada last year, it probably earned more than you did. Rising housing costs destroy neighbourhoods, force endless hours of commute time and sooner or later hobble innovation. Workers compete against their own interests just to gain access to the wealthy, while simultaneously sliding downwards and away. Capitalists naturally collect exorbitant rents, in the broader, economic sense of the word, or make capital gains on every asset they possess or control and which everyone else really covets. They do this routinely because they can. You may despise such exploitive people, but your own success may require that you have access to them.Governments and central banking agencies often make unequal conditions worse without introducing real offsetting benefits. This can take the form of throwing good money after bad (supporting dying enterprises rather than investing in growing ones), giving large enterprises unconditional bailouts, and pursuing interest rate suppression-arguably the worst growth killer. When wages are depressed by low demand for labour, central banks are persuaded to keep interest rates low hoping to help the unemployed and underpaid subsist. In turn, investors sit on their money or turn to whatever high-yield low-risk opportunities remain. Unless an angel fund or public initiative underwrites needed riskier options, nobody goes there. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,031

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0060,013
Communication savante0,0100,009
Science ouverte0,0010,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,035
Tête enseignante GPT0,239
Écart entre enseignants0,204 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations25
Publié2017
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revue˜The œinnovation journalMême sujetEconomic Development and Digital TransformationTravaux en français237 207