Sentence examples for your reflective from inspiring English sources

★ ARIES 21 Mar-19 Apr Your reflective side (some astrologers doubt Rams have any such thing) is not exactly encouraged by the month of Sagittarius, a fellow fire sign.

It adds: "We would have welcomed your reflective thoughts as to the cause of this unlawful behaviour; was it incompetence and/or malicious?" The letter, dated 15 April, says Blake offers nothing in her letter "that might break the culture of bad practice (to be defended at taxpayer expense) that has been shown by the case to exist in our borough".

Entry was ticketed by mirror, it was free but the artists asked you leave your reflective token behind in an area of the space that spoke to you.

The thing about journaling is that if you write in a journal every day, it will turn into a habit that will develop your reflective ability to be more aware and present, all while being able to make sense of your emotions.

But in your reflective essay you mention a lack of interest.

Apply your reflective surface.

The title is a riff on the Wallace Stevens poem "Thirteen Ways of Looking at a Blackbird," but much of the contents also conjure the Paul Simon song "Fifty Ways to Leave Your Lover": reflective, yes, but also resigned, repetitive and thematically ambivalent.

Be proud of the fact that your are reflective and think before you speak or act.

In other words, just because other people do or use something effectively isn't a sign that it will suit you too; you need to put your own reflective mind to work on each situation to decide whether it will be a fit for you, your lifestyle, and those around you directly impacted by your decisions.

Your music is very reflective, so your set will be a good time for festival punters to take stock of the obscenities committed throughout the previous few days.

It isn't always vital, and it might not always be possible, but in any research that wants to draw conclusions stretching beyond the people that have been directly researched themselves, it is crucial to understand how reflective your dataset is of your target population.