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Record W2178354601

Cities, Innovation, and the Future

2015· article· en· W2178354601 on OpenAlexaboutno aff
Langdong Morris

Bibliographic record

VenueInternational management review · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsThrivingBoomPopulationInvestment (military)Real estateCapital (architecture)BusinessEconomic growthPoliticsMarketingPublic relationsSociologyPolitical scienceEconomicsGeographyEngineeringSocial scienceLawFinance
DOInot available

Abstract

fetched live from OpenAlex

Innovation is intimately linked with cities. This occurs for many reasons, many of which are entirely obvious. People congregate in cities, and through experiencing problems and sharing ideas for how to solve them, innovation comes about. There are suppliers and experts and scholars and materials and tinkerers in cities in abundance, so questions can be formulated and answered. There is capital in cities, to provide investment to support good ideas that solve problems which people are willing to pay for. There are people in cities looking for better opportunities, and who hire on when new companies scale up.But the city itself is also a topic for innovation. These are the fields of urban design, city planning, real estate development, construction, and architecture, which come together to shape the human-created environment in which now more than 3.5 billion people live. Demographers estimate that by 2100, the total aggregate urban population will be around 7.5 billion, meaning that over the next 85 years, humanity will construct new urban settings for 4 billion people. This will certainly constitute the most massive building boom in history.But what will these cities look like? How will they feel? What will it be like to live in them? Will they be squalid and polluted? Will they be the playground of cars and the bane of pedestrians? Will they be healthy and thriving, or sick and tired? Here are some interesting facts about today's cities, which tell us a lot about what we may want and not want for tomorrow's.People who have longer commute times today are less happy than people with shorter commute times. It can take up to an hour for people to recover the ability to concentrate following a long commute, and psychologists have a word for this. They call it amnesia, which occurs as people simply shut out stimulus and try to forget about their long drive as soon as it is over. The longer the commute, the more likely people are to report chronic pain, high cholesterol, and people with commutes longer than 90 minutes are the most likely to be anxious, tired, and obese.Public health experts have invented a word to describe low density suburban neighborhoods where one is obliged to drive everywhere due to the dispersion of housing and shopping and the massive highways that separate everything from everything else: obesogenic. That is, suburbia literally makes people fat, because they spend too much time driving, and not enough time walking. Imagine designing a city that is intended to make people overweight! But this is precisely what we have done ...Consequently, merely living in a sprawling, suburb-oriented community has the effect of reducing one's expected life span by four years, largely as a consequence of the diseases associated with obesity and the stress of the commuter lifestyle. In contrast with the negative impacts of disbursed suburbia, some cities have combined dense urban living arrangements in configurations that are quite pleasant, and to which people who have choice are inevitably drawn. Vancouver, Canada, is one of those cities, and the real estate development profession has created a new word to describe it: Vancouverism. Vancouver is relentlessly dense and yet manages to be charming, beautiful, and humane. It helps that the setting is so spectacular, but even without the water and the mountains, the lessons of thoughtful zoning and planning are applicable anywhere. Developers are copying Vancouver wherever they can.When thinking about city street, scholars have identified what is now referred to as the law of social geometry, which tells us about how far from the street a good porch should be. It must be close enough to allow the porch sitter to interact with the passing pedestrian, but far enough that they are not obliged to interact. Stunningly, this can be quantified. The perfect distance for urban street conviviality is 10.6 feet.However, if the cars take over a neighborhood, the results can be disastrous for the human and humane scale. …

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)0.001
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.785
Threshold uncertainty score0.279

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 studies0.0000.000
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 head0.028
GPT teacher head0.260
Teacher spread0.231 · 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
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
Published2015
Admission routes1
Has abstractyes

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