poor models

USAGE SUMMARY

The phrase "poor models" is correct and usable in written English.
It can be used to describe models that are inadequate, ineffective, or of low quality in various contexts, such as scientific research, data analysis, or theoretical frameworks. Example: "The study's conclusions were questionable due to the reliance on poor models that failed to accurately represent the data."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

44 human-written examples

People have very poor models of how to be angry in a warm, creative, connected way.

The New York Times - Science

Third, we worry that shorter, single-study articles can be poor models of science.

The New York Times

It's got high and low, rich and poor, models and bike messengers, an incredible array of humankind that flows like a river in both directions.

The New York Times - Travel

Poor models.

TechCrunch

And after playing LA Noire, the poor models, poor voice acting, and poor lip syncing are doubly disappointing.

TechCrunch

Users of Version 1, in about half the cases, selected poor models with high forecast error.

Omega

Human-verified similar examples from authoritative sources

Similar Expressions

15 human-written examples

You don't need to ensure they look good by making your poor, hapless models look as hideous as possible.

The Guardian - Lifestyle

Charles had a son, about 16, and he always feared he was a poor model for him.

The New Yorker

The overwhelming scholarly assessment is that the ruling in Bush v. Gore is a poor model of judicial reasoning.

The New York Times - Books

The company's poor model range and slow product development has been exposed to real competition.

The Economist

4.30pm Pity the poor model who whacked her head - the make up mark was visible from the back of the crowd - at the sustainable fashion show.

The Guardian - Lifestyle

Expert writing Tips

Best practice

When discussing scientific or technical topics, clearly specify the criteria used to evaluate the models as "poor models", such as accuracy, predictive power, or fit to experimental data. This provides context and strengthens your argument.

Common error

Avoid simply stating that models are "poor models" without providing specific evidence or justification. Explain why the models are considered poor and what limitations they possess. Generic statements can weaken your analysis.

Linguistic Context

The phrase "poor models" functions primarily as a descriptive phrase, where 'poor' acts as an adjective modifying the noun 'models'. It serves to categorize or characterize models as being of low quality or effectiveness. Ludwig AI's analysis confirms its use in various contexts.

Expression frequency: Very common

Frequent in

Science

54%

News & Media

42%

Formal & Business

4%

Less common in

Ludwig's WRAP-UP

In summary, "poor models" is a grammatically correct and frequently used phrase, particularly in scientific and news-related contexts, to describe models that are inadequate or ineffective. Ludwig AI confirms its usability and provides various examples. When using this phrase, it's crucial to provide specific reasons or justifications for the assessment, as overgeneralization can weaken the impact. Alternative phrases like "inadequate models" or "deficient models" can also be used, depending on the desired nuance. Overall, understanding the context and providing clear explanations are essential for effective communication when discussing "poor models".

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

inadequate models

This alternative focuses on the insufficiency of the models to fulfill their intended purpose.

deficient models

This alternative highlights the lack of essential qualities or elements in the models.

substandard models

This alternative emphasizes that the models fall below an accepted level of quality.

inferior models

This alternative suggests that the models are lower in rank or quality compared to others.

weak models

This alternative describes models that are not robust or effective.

flawed models

This alternative emphasizes the presence of imperfections or errors in the models.

unreliable models

This alternative focuses on the lack of dependability or trustworthiness of the models.

faulty models

This alternative suggests that the models have defects that impair their function.

inaccurate models

This alternative emphasizes that the models do not provide correct or precise results.

simplistic models

This alternative indicates that the models are overly simplified and fail to capture the complexity of the real world.

FAQs

How can I use "poor models" in a scientific context?

In scientific writing, "poor models" can be used to describe models that fail to accurately represent real-world phenomena or make reliable predictions. It's crucial to specify the criteria that make the models inadequate, such as low accuracy or lack of fit with experimental data.

What are some alternatives to saying "poor models"?

Depending on the context, you could use alternatives such as "inadequate models", "deficient models", or "substandard models". The best choice depends on the specific nuance you want to convey.

Is it appropriate to use "poor models" in formal writing?

Yes, "poor models" is appropriate for formal writing, especially in scientific and technical contexts. However, ensure that you provide clear justification for why the models are considered poor and avoid overly subjective assessments.

How can I improve "poor models"?

Improving "poor models" typically involves refining the underlying assumptions, incorporating more relevant data, or developing more sophisticated algorithms. It's essential to identify the specific limitations of the models and address them systematically.